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In this article, with the help of Heidegger and Foucault's conceptual tools, as well as the achievements of the cognitive science, we try to examine the transition from paper reading to digital reading. This discussion can be a preparation for a philosophical understanding of the digital age. We show that Heidegger's analysis of the ready-to-hand beings and technology can help to understand the reading behaviors of paper and digital readers. We have also use Heidegger's analytical framework for text ontology. On the other hand, Foucault's reflections on the embodied technologies can explain the power-knowledge relationships that is constructed around the reader. In addition, the cognitive science has provided detailed empirical findings on the effects of reading behaviors on the human cognitive biases and skills by examining the various modes of reading. Embodied and skillful cognitive science, by going beyond the computational understanding of human beings, has noticed the various behaviors and states of the body in reading processes and highlighted their effects. To integrate these areas of research, we try to place the findings of the cognitive science within the framework of Heidegger and Foucault's technological understanding of the modern power-knowledge relationships. [ABSTRACT FROM AUTHOR]

Abstract concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological issues, and recommendations for future research. In this paper, we urge researchers to go beyond the traditional abstract-concrete dichotomy and consider the multiple dimensions that characterize concepts (e.g., sensorimotor experience, social interaction, conceptual metaphor), as well as the mediating influence of linguistic and cultural context on conceptual representations. We also promote the use of interactive methods to investigate both the comprehension and production of abstract concepts, while also focusing on individual differences in conceptual representations. Overall, we argue that abstract concepts should be studied in a more nuanced way that takes into account their complexity and diversity, which should permit us a fuller, more holistic understanding of abstract cognition. [ABSTRACT FROM AUTHOR]

Reading primary research literature is an essential skill for all scientists and students on science degree programmes, however little is known about how researchers at different career stages interact with and interpret scientific papers. To explore this, we conducted a survey of 260 undergraduate students and researchers in Biological Sciences at a research intensive UK university. Responses to Likert scale questions demonstrated increases in confidence and skill with reading the literature between individuals at each career stage, including between postdoctoral researchers and faculty academics. The survey indicated that individuals at different career stages valued different sections of scientific papers, and skill in reading the results section develops slowly over the course of an academic career. Inexperienced readers found the methods and results sections of research papers the most difficult to read, and undervalued the importance of the results section and critical interpretation of data. These data highlight a need for structured support with reading scientific literature at multiple career stages, and for senior academics to be aware that junior colleagues may prioritise their reading differently. We propose a model for the development of literature processing skills, and consider the need for training strategies to help inexperienced readers engage with primary literature, and therefore develop important skills that underpin scientific careers. We also encourage researchers to be mindful of language used when writing papers, and to be more inclusive of diverse audiences when disseminating their work. [ABSTRACT FROM AUTHOR]

The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing. [ABSTRACT FROM AUTHOR]

The need to complete multiple tasks concurrently is a common occurrence both daily life and in occupational activities, which can often include simultaneous cognitive and physical demands. As one example, there is increasing availability of head-worn display technologies that can be employed when a user is mobile (e.g., while walking). This new method of information presentation may, however, introduce risks of adverse outcomes such as a decrement to gait performance. The goal of this study was thus to quantify the effects of a head-worn display (i.e., smart glasses) on motor variability during gait and to compare these effects with those of other common information displays (i.e., smartphone and paper-based system). Twenty participants completed four walking conditions, as a single task and in three dual-task conditions (three information displays). In the dual-task conditions, the information display was used to present several cognitive tasks. Three different measures were used to quantify variability in gait parameters for each walking condition (using the cycle-to-cycle standard deviation, sample entropy, and the “goal-equivalent manifold” approach). Our results indicated that participants used less adaptable gait strategies in dual-task walking using the paper-based system and smartphone conditions compared with single-task walking. Gait performance, however, was less affected during dual-task walking with the smart glasses. We conclude that the risk of an adverse gait event (e.g., a fall) in head-down walking conditions (i.e., the paper-based system and smartphone conditions) were higher than in single-task walking, and that head-worn displays might help reduce the risk of such events during dual-task gait conditions. [ABSTRACT FROM AUTHOR]

This paper aims to show that properties of cognitive/conceptual representations and formal‐logical structures of linguistic meaning can be inter‐translated, recast, transformed into one another, and so united together, even though cognitive/conceptual representations and formal‐logical structures of linguistic meaning are apparently distinct in ontology and divergent in their form or character. While cognitive/conceptual representations are ultimately rooted in sensory‐motor systems, formal‐logical structures of linguistic meaning are abstractions detached from and independent of the actualized world. This paper sketches out the foundations of how representations of linguistic meaning in terms of cognitive/conceptual structures in Cognitive/Conceptual Semantics can be unified with those in terms of formal‐logical structures in Formal Semantics. This is done by recasting cognitive/conceptual representations in terms of formal‐logical structures of linguistic meaning and re‐encoding formal‐logical structures of linguistic meaning in terms of cognitive/conceptual representations. Then, these two types of semantic representations, thus shown representationally equivalent, will be related to a series of derivations across levels in neuronal networks and dynamics. The general discussion on unifying cognitive/conceptual representations of linguistic meaning with formal‐logical structures is contextualized within the broader context of theorizing in cognitive science. [ABSTRACT FROM AUTHOR]

Do highly productive researchers have significantly higher probability to produce top cited papers? Or do high productive researchers mainly produce a sea of irrelevant papers—in other words do we find a diminishing marginal result from productivity? The answer on these questions is important, as it may help to answer the question of whether the increased competition and increased use of indicators for research evaluation and accountability focus has perverse effects or not. We use a Swedish author disambiguated dataset consisting of 48.000 researchers and their WoS-publications during the period of 2008–2011 with citations until 2014 to investigate the relation between productivity and production of highly cited papers. As the analysis shows, quantity does make a difference. [ABSTRACT FROM AUTHOR]

The growing integration of renewable energy sources into grid-connected microgrids has created new challenges in power generation forecasting and energy management. This paper explores the use of advanced machine learning algorithms, specifically Support Vector Regression (SVR), to enhance the efficiency and reliability of these systems. The proposed SVR algorithm leverages comprehensive historical energy production data, detailed weather patterns, and dynamic grid conditions to accurately forecast power generation. Our model demonstrated significantly lower error metrics compared to traditional linear regression models, achieving a Mean Squared Error of 2.002 for solar PV and 3.059 for wind power forecasting. The Mean Absolute Error was reduced to 0.547 for solar PV and 0.825 for wind scenarios, and the Root Mean Squared Error (RMSE) was 1.415 for solar PV and 1.749 for wind power, showcasing the model's superior accuracy. Enhanced predictive accuracy directly contributes to optimized resource allocation, enabling more precise control of energy generation schedules and reducing the reliance on external power sources. The application of our SVR model resulted in an 8.4% reduction in overall operating costs, highlighting its effectiveness in improving energy management efficiency. Furthermore, the system's ability to predict fluctuations in energy output allowed for adaptive real-time energy management, reducing grid stress and enhancing system stability. This approach led to a 10% improvement in the balance between supply and demand, a 15% reduction in peak load demand, and a 12% increase in the utilization of renewable energy sources. Our approach enhances grid stability by better balancing supply and demand, mitigating the variability and intermittency of renewable energy sources. These advancements promote a more sustainable integration of renewable energy into the microgrid, contributing to a cleaner, more resilient, and efficient energy infrastructure. The findings of this research provide valuable insights into the development of intelligent energy systems capable of adapting to changing conditions, paving the way for future innovations in energy management. Additionally, this work underscores the potential of machine learning to revolutionize energy management practices by providing more accurate, reliable, and cost-effective solutions for integrating renewable energy into existing grid infrastructures. [ABSTRACT FROM AUTHOR]

Ignorance, or the lack of knowledge, appears to be steadily spreading, despite the increasing availability of information. The notion of informed ignorance herein proposed to describe the widespread position of being exposed to an abundance of information yet lacking relevant knowledge, which is tied to the exponential growth in misinformation driven by technological developments and social media. Linked to many of societies' most looming catastrophes, from political polarization to the climate crisis, practices related to knowledge and information are deemed some of the most imminent and daunting modern threats, evidenced by the latest report of the World Economic Forum, which has named misinformation the most severe short-term global risk. This paper's epistemic perspective links the properties of today's information culture and the ways in which it interacts with individual capacities and limitations in current technological and socio-political contexts. Such a position is analyzed through the lens of epistemic principles as a contemporary epistemic phenotype that emerges from an environment of ill-adapted and excessive information inputs and leads to a distinctive type of social injustice that is primarily epistemic in nature. While equity and accessibility are widely discussed as important contributing factors to epistemic discrepancies, other overlooked but fundamental issues underlying epistemic injustices are considered, such as information manipulation, cognitive limitations, and epistemic degradation. To effectively face this elusive threat, we propose an inclusive viewpoint that harnesses knowledge from cognitive science, science and technology studies, and social epistemology to inform a unifying theory of its main impacts and driving forces. By adjusting a modern epistemic framework to the described phenomena, we intend to contextually outline its trajectory and possible means of containment based on a shared responsibility to maintain ethical epistemic standards. In a time of international unrest and mounting civil acts of violence, it is pertinent to emphasize the ethical principles of knowledge systems and authorities and suggest policy adaptations to maintain a social contract based on the shared values of truth and freedom. [ABSTRACT FROM AUTHOR]

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies. [ABSTRACT FROM AUTHOR]

Cognitive communication research with Chinese characteristics is both the theoretical innovation and practical exploration in the interdisciplinary fields of communication and cognitive science. In recent years, under the context of interdisciplinary research, cognitive communication research in China is no longer limited to the discussion of its disciplinary boundary and its legitimacy. According to the former literature, researchers have discussed the three main topics of cognitive communication: the knowledge system of cognitive communication, the framework of cognitive neurocommunication and the applied research of cognitive communication. However, the discipline construction of cognitive communication in China is still in the stage of exploration. Both how to form an independent and original cognitive communication knowledge system and how to put the theoretical vision in the local context and respond to the social problems need to be explained and to be closely integrated with Chinese characteristics in the cognitive communication research. In order to systematically illustrate the Chinese characteristics of cognitive communication research, this paper focuses on four basic questions: what to construct, why to construct, how to construct and what to do. Then, this paper constructs a four-dimensional framework which includes the value system, the dynamic system, the knowledge production system and the application system. This paper (1) discusses the theoretical construction with Chinese characteristics in the value system. (2) integrates the background of disciplinary development and the trend of technological development into the dynamic system of cognitive communication research. (3) focuses on the theoretical innovation based on practice in the knowledge production system. (4) then explores the implement of cognitive communication with Chinese characteristics in overall strategic needs of the country. This study suggests that, under the construction of philosophy and social sciences with Chinese characteristics, cognitive communication with Chinese characteristics needs to ascertain the value orientation, characteristic and research objective. Under the impetus of practice power, discipline development power and tool power, cognitive communication continues to have Chinese characteristics. Cognitive communication with Chinese characteristics needs to be completed in terms of establishing the guiding position of Marxism, integrating multi-theory and solving important problems, which can reflect Chinese characteristics in academic research, theoretical construction and problem-orientation. Finally, in the insight of cognitive pattern, exploration of cognitive mechanism and innovation of cognitive tools, the research result of cognitive communication can be used in practical applications. Compared to previous research, this paper has made extensions in the following aspects: Firstly, this paper has constructed the interactive and complex four-dimensional framework for the study of cognitive communication with Chinese characteristics, which suggests the essential requirements of Chinese characteristics in cognitive communication. At the same time, it explores the approach to the local study of cognitive communication, hoping to establish a subject status in constructing original theories, to keep up with local practice and respond to real problems. Secondly, this paper, closely related to the practice of socialist construction with Chinese characteristics, explores the possible practical aspects of cognitive communication, aiming at exploring and solving real problems. The four-dimensional framework helps to explicit the essence, the development motivation, the implementation approach and the application of the study of cognitive communication with Chinese characteristics, which helps to form the Chinese style of cognitive communication, to expand the Chinese research team of cognitive communication, and to infuse Chinese style into the international academic exchange of cognitive communication, which makes the future cognitive communication research move towards the construction direction of "Chinese characteristics" and finally, the cognitive communication discipline with Chinese characteristics will be constructed. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on the topics including demonstrates exciting results based on self-imitation learning within a cross-modal setting; and providing advances in controllable generation and interpolation across attributes.

An editorial is presented which discusses the collaborative writing with multiple authors which has additional challenges including varied levels of engagement of coauthors, provision of fair credit through authorship or acknowledgements and acceptance of diversity of work styles. Also discussed are the 10 simple rules for collaboratively writing a multi-authored paper which include to build a writing team wisely; to create a data management plan and to jointly decide on authorship guidelines.

The victories of the Go-playing artificial intelligence (AI) "AlphaGo" against professional player Lee Sedol in 2016 had a profound impact on public and academic perceptions of AI. This event shocked observers, as the ability of a machine to defeat a world champion human in a highly complex game seemed to indicate that a machine had achieved human-like—or more than human—intelligence. But why was AlphaGo so readily anthropomorphized by academic and non-academic audiences alike? Drawing from existing analyses of reactions to and arguments concerning AlphaGo and AI generally, this paper argues that "generative" cognitive science—a school of thought exemplified by the linguistic work of Noam Chomsky—offers two novel contributions to this subject. First, generativism sheds light on an irrational double standard in the study of the human mind in contrast to the study of non-cognitive systems—"methodological dualism"—which, I argue, has been transferred to evaluations of AlphaGo and other AI. Second, by exposing this irrational double standard in perceptions of AI, I employ generativism's more well-known arguments concerning the nature of human intelligence and its scientific study to the evaluation of AI, exposing deficient interpretations widely used in the case of AlphaGo and AI generally. [ABSTRACT FROM AUTHOR]

Researchers in cognitive science have long been interested in modeling human perception using statistical methods. This requires maneuvers because these multiple dimensional data are always intertwined with complex inner structures. The previous studies in cognitive sciences commonly applied principal component analysis (PCA) to truncate data dimensions when dealing with data with multiple dimensions. This is not necessarily because of its merit in terms of mathematical algorithm, but partly because it is easy to conduct with commonly accessible statistical software. On the other hand, dimension reduction might not be the best analysis when modeling data with no more than 20 dimensions. Using state-of-the-art techniques, researchers in various research disciplines (e.g., computer vision) classified data with more than hundreds of dimensions with neural networks and revealed the inner structure of the data. Therefore, it might be more sophisticated to process human perception data directly with neural networks. In this paper, we introduce the multi-dimensional data analysis platform (MuDAP), a powerful toolbox for data analysis in cognitive science. It utilizes artificial intelligence as well as network analysis, an analysis method that takes advantage of data symmetry. With the graphic user interface, a researcher, with or without previous experience, could analyze multiple dimensional data with great ease. [ABSTRACT FROM AUTHOR]

In his article in Science, Nicolas Gisin claimed that quantum correlations emerge from outside space–time. We explainthat they are due to space-time symmetries. This paper is a critical review of metaphysical conclusions found in many recent articles. It advocates the importance of contextuality, Einstein -causality and global symmetries. Bell tests allow only rejecting probabilistic coupling provided by a local hidden variable model, but they do not justify metaphysical speculations about quantum nonlocality and objects which know about each other's state, even when separated by large distances. The violation of Bell inequalities in physics and in cognitive science can be explained using the notion of Bohr- contextuality. If contextual variables, describing varying experimental contexts, are correctly incorporated into a probabilistic model, then the Bell–CHSH inequalities cannot be proven and nonlocal correlations may be explained in an intuitive way. We also elucidate the meaning of statistical independence assumption incorrectly called free choice, measurement independence or no- conspiracy. Since correlation does not imply causation, the violation of statistical independence should be called contextuality; it does not restrict the experimenter's freedom of choice. Therefore, contrary to what is believed, closing the freedom-of choice loophole does not close the contextuality loophole. [ABSTRACT FROM AUTHOR]

The Free Energy Principle (FEP) and Integrated Information Theory (IIT) are two ambitious theoretical approaches. The first aims to make a formal framework for describing self-organizing and life-like systems in general, and the second attempts a mathematical theory of conscious experience based on the intrinsic properties of a system. They are each concerned with complementary aspects of the properties of systems, one with life and behavior, the other with meaning and experience, so combining them has potential for scientific value. In this paper, we take a first step towards such a synthesis by expanding on the results of an earlier published evolutionary simulation study, which show a relationship between IIT-measures and fitness in differing complexities of tasks. We relate a basic information theoretic measure from the FEP, surprisal, to this result, finding that the surprisal of simulated agents' observations is inversely related to the general increase in fitness and integration over evolutionary time. Moreover, surprisal fluctuates together with IIT-based consciousness measures in within-trial time. This suggests that the consciousness measures used in IIT indirectly depend on the relation between the agent and the external world, and that it should therefore be possible to relate them to the theoretical concepts used in the FEP. Lastly, we suggest a future approach for investigating this relationship empirically. Author summary: Two influential theoretical frameworks in cognitive science, neuroscience and computational biology, are the Free Energy Principle and Integrated Information Theory. The first is a formal approach to self-organization and adaptive behavior ‐ in short, life ‐ based on first principles from statistical physics. The second is an attempt at formally describing the intrinsic experience of a given system, that is, how it feels to be that system. In this way, these two theories provide tools for understanding two complementary aspects of a given organism; namely, how it acts in a goal-directed manner based on statistical beliefs about the world, and how it feels to be that system in that process. In this paper, we provide an initial numerical investigation of the potential relation of these theoretical frameworks. We simulate agents that undergo evolution, and show that as their level of integration (Φ, a measure from Integrated Information Theory) increases, information theoretic surprisal (a quantity used in the Free Energy Principle) decreases. We also see that Φ and surprisal fluctuate together, and that these fluctuations depend on sensory input. Finally we provide considerations for future simulation work, and how to bring these two theoretical frameworks closer together. [ABSTRACT FROM AUTHOR]

Right now one of remarkable features of clashes between countries is frequent cognitive warfare. In order to control emotions of the public, US and Western countries use a lot of theories on cognitive dissonance and psychodynamics to develop information and publicity in grey zone when facing enemy countries. But related researches always rely on traditional frames of strategic communication to understand the new kind of warfare, neglecting the beginning of cognitive turn of strategic communication or the important effects of cognitive sciences on the core logic of traditional strategic communication. This paper uses paradigms of cognitive sciences, securitization, semiotics and narratives to analyze critical topic field of cognitive strategic communication and indicates the research propositions of public opinion and group communication in cyber space, which are divided into two strategies of cultivating KOL to lead good opinions and constructing commonwealth or fighting enemies in bias of emotions. The ultimate pursuit of cognitive strategic communication is general national security, which includes three approaches of breaking information lockout, carrying out strategic deception and defending non-material territories. In realities, cognitive strategic communication always focuses on practices of new public diplomacy that demonstrate in manipulating narratives and spreading strong symbols for reconstructing“brain frontier”of the public of rivals. This paper concludes that national narrative ability and symbol spreading ability should be promoted unceasingly, the basic constructions, theoretical schema, system mechanism of cognitive strategic communication must be improved in the future. Compared with related documents, this paper hopes to make innovations as followings: (1) start a new academic sphere by integrating paradigms of politics, communication studies, military science, national security science, psychology, narratives, semiotics and break the stereotype of detecting strategic communication or national security under one perspective; (2) put forward an important concept of cognitive strategic communication under the grand frame of national security, upgrade the traditional system of strategic communication and meet theoretical requirements of cognitive warfare in practice; (3) the raising of cognitive strategic communication is expected to take the lead of western academic research in the related fields and complete discourse transformation; (4) link the science of journalism and communication with national security for the first time and illustrate the importance and urgency of breaking information monopoly and defending non-material territories. This paper penetrates self-speech and industry regulation of information single discipline of science, marches on complex dimension of multi-disciplinary cross connection; Based on the connecting historic context and global background, this paper emphasizes the combination of world vision and Chinese text, Chinese expression, Chinese ideas, which is an important research on theories of international communication with Chinese characteristics. [ABSTRACT FROM AUTHOR]

The prosperity of Chinese philosophy and social sciences necessitates knowledge independence and theoretical innovation, which in turn guides the mission and direction of academic maturity and development. Chinese cognitive communication research originated from the trend of our epoch of cognitive turn responding to the development needs of the breakthrough of the communication discipline. As a result, the cross-boundary dialogue and convergence of multiple knowledge were stimulated, benefiting its interdisciplinary characteristics. This discipline gradually completed the transformation of the "Chinese style" discipline and became a fresh experience of the construction of the New Liberal Arts Initiative (NLAI) after more than ten years of path exploration. However, Chinese cognitive communication research is still in a dilemma of interdisciplinary research which emphasizes the importance of facing the suspicion and pain of discipline legitimacy by forming self-awareness of a fully-fledged academic subject through articulating the position, establishing the independent scientific principle, clearing a self-consistent value of the academic and forming a deep consciousness of Chinese discipline construction. This paper systematically examined 979 articles sourced from CSSCI using the formalism approach. The goal is to inspect the disciplinary practice and characteristics of Chinese cognitive communication research, predict its transformation into a fully-fledged academic subject, and illuminate its way of promoting disciplinary consciousness. The results show that the "disciplinary exploration" of Chinese cognitive communication research was executed from the aspects of "positioning", "practice" and "organization". Nevertheless, this discipline is trapped in the path of dependence induced by inflexible means of interdisciplinary research and its outlook is overshadowed by the contradictory properties of disciplinary, which forces it to pursue innovative structural thinking, firmly anchored in a bedrock of shared values, while simultaneously embracing the dynamism inherent in distinctive creation in order to tackle these hurdles. So it’s imperative to undertake a meticulous examination of the field of this discipline involving scrutinizing the logical framework of knowledge, which is established through the development of a well-defined conceptual system, and making dedicated efforts toward advancing theoretical innovation. The impediments that hinder this emerging discipline may be overcome by confronting the challenges brought about by cutting-edge technology, engaging in inter-civilizational learning to assimilate cognitive knowledge from various cultures around the world, leveraging the enriching discourse resources of classical Chinese philosophy, and re-evaluating the humanistic implications of Chinese cognitive communication research, based on which it can reconstruct the domain of research via the consistent and coherent logical connotation of the methods and discourse. In this way, Chinese cognitive communication research will be transformed into a comprehensive insight into the live world and take the main responsibility of governance decisions and scientific prosperity. Compared with previous studies, this paper tries to integrate the academic frontier and Chinese context, combining the latest achievements of cognitive science and ancient Chinese cognitive wisdom. The thinking model was constructed on the basis of the systematic literature review, with the help of diversified knowledge paradigms to lead this discipline to the path of knowledge independence and broad domain. According to this idea, Chinese cognitive communication research will incorporate literature and function, promoting mutual learning and coexistence of civilizations, advancing human digital civilization, and Chinese modernization. [ABSTRACT FROM AUTHOR]

The Nibbānasukha-sutta contains Sāriputta's statement that the pleasure (sukha) of nibbāna lies in the fact that nothing is experienced (vedayita). This statement may be seen as complementary to the proclamation in the Kaḷāra-sutta that all that is experienced is unpleasant (dukkha). In this paper, I attempt to reconstruct the ideas serving as a philosophical backdrop to these radical and seemingly counterintuitive claims. I use a comparative and interdisciplinary approach, re-examining several key Nikāya passages, as well as drawing on modern cognitive science and philosophy of mind. I suggest that vedayita and the closely related concept of the five khandhas (and in particular viññāṇa) refer to various aspects of the type of consciousness whose content is phenomenal, introspectable, reportable and may be integrated into memory. I suggest that such consciousness is not a constant feature of our being engaged in the world and that its absence does not entail insentience or being incognizant. I hypothesize that a relatively low frequency of occurrences of such consciousness in the states known as absorption or flow contributes to their pleasurable nature and the altered sense of the passage of time and selfhood. I attempt to explain how the presence or absence of such consciousness is related to the states of dukkha or sukha, with particular focus on the role played by saṅkhāra. I also discuss the limits of introspection as a means of understanding what exactly makes experiences pleasurable or painful, and consider the possibility of non-introspectable forms of pleasure. In conclusion, I suggest that psychological transformation in early Buddhism is connected with a radical change of perspective, which involves no longer identifying with one's own consciousness. [ABSTRACT FROM AUTHOR]

We propose the "runtime learning" hypothesis which states that people quickly learn to perform unfamiliar tasks as the tasks arise by using task-relevant instances of concepts stored in memory during mental training. To make learning rapid, the hypothesis claims that only a few class instances are used, but these instances are especially valuable for training. The paper motivates the hypothesis by describing related ideas from the cognitive science and machine learning literatures. Using computer simulation, we show that deep neural networks (DNNs) can learn effectively from small, curated training sets, and that valuable training items tend to lie toward the centers of data item clusters in an abstract feature space. In a series of three behavioral experiments, we show that people can also learn effectively from small, curated training sets. Critically, we find that participant reaction times and fitted drift rates are best accounted for by the confidences of DNNs trained on small datasets of highly valuable items. We conclude that the runtime learning hypothesis is a novel conjecture about the relationship between learning and memory with the potential for explaining a wide variety of cognitive phenomena. Author summary: Human cognition is remarkably flexible, with the ability to reliably perform a wide variety of tasks, including idiosyncratic and unfamiliar ones, in a wide variety of contexts. However, despite impressive advances in machine learning, leading to artificial intelligences capable of outperforming humans on select individual tasks, this flexibility has yet to be replicated by computational models. Doing so is essential to both creating general artificial intelligence and to achieving a deeper understanding of the human brain and mind. To account for this vital property of human cognition, we introduce the "runtime learning hypothesis", in which the brain rapidly constructs task-specific models in response to the needs of the moment using an internal training process based on valuable exemplars of the relevant concepts. We examine the plausibility of this hypothesis using human behavioral experiments and machine-learning-based computational modeling. The results are consistent with the human brain using runtime learning to flexibly perform tasks. [ABSTRACT FROM AUTHOR]

Vision and Language Navigation (VLN) is a task in which an agent needs to understand natural language instructions to reach the target location in a real-scene environment. To improve the model ability of long-horizon planning, emerging research focuses on extending the models with different types of memory structures, mainly including topological maps or a hidden state vector. However, the fixed-length hidden state vector is often insufficient to capture long-term temporal context. In comparison, topological maps have been shown to be beneficial for many robotic navigation tasks. Therefore, we focus on building a feasible and effective topological map representation and using it to improve the navigation performance and the generalization across seen and unseen environments. This paper presents a S elf-organizing Memory based on Adaptive Resonance Theory (SMART) module for incremental topological mapping and a framework for utilizing the SMART module to guide navigation. Based on fusion adaptive resonance theory networks, the SMART module can extract salient scenes from historical observations and build a topological map of the environmental layout. It provides a compact spatial representation and supports the discovery of novel shortcuts through inferences while being explainable in terms of cognitive science. Furthermore, given a language instruction and on top of the topological map, we propose a vision–language alignment framework for navigational decision-making. Notably, the framework utilizes three off-the-shelf pre-trained models to perform landmark extraction, node–landmark matching, and low-level controlling, without any fine-tuning on human-annotated datasets. We validate our approach using the Habitat simulator on VLN-CE tasks, which provides a photo-realistic environment for the embodied agent in continuous action space. The experimental results demonstrate that our approach achieves comparable performance to the supervised baseline. [ABSTRACT FROM AUTHOR]

Resilience is a basic trait of cognitive systems and fundamentally connected to their autopoietic organization. It plays a vital role in maintaining the identity of cognitive systems in the face of external threats and perturbances. However, when examining resilience in the context of autopoiesis, an overlooked issue arises: the autopoietic theory formulated by Maturana and Varela (1980) renders traditional Shannon information obsolete, highlighting that information should not be ascribed a role in cognitive systems in a general sense. This paper examines the current situation and suggests a possible way forward by exploring an affordance-based view on information, derived from radical cognitive science, which is exempted from Maturana and Varela's critique. Specifically, it argues that the impact of social influence on affordance use is crucial when considering how resilience can manifest in informational relations pertaining to the human cognitive ecology. [ABSTRACT FROM AUTHOR]

Nowadays some debates exist within psychological and neuropsychological assessment fields respecting differences between traditional testing (with pencil and paper) and the same tasks implemented via computer or Tablet programs. In this context, the Mode Effect is defined as the effect by which the same tasks, tested with different devices, may show different results. In addition, the Mode Effect might be associated with higher cognitive load, higher attentional requirements, fatigue and stress among others. The Corsi block-tapping test is widely used in psychology and cognitive sciences to assess visuospatial working memory. Originally, the stimuli sequence was manually set by a researcher which could entail a constraint to run the test accurately. Today, there are many digital versions available for computers or tablets and, although this meant a significant cut on manual steps, there are discussions on the impact these digital versions could have on working memory as opposed to traditional ones. This work focuses on the development of the CorsiBot: a new physical and automated version that enables researchers to assess performance and resolution strategies for the Corsi block-tapping test while combining the benefits of both tangible and digital versions. In addition, this work aimed to compare the performance of a sample of adults between a digital version of Corsi and our CorsiBot. Thirty adults where assessed with both devices with different protocols. After each assessment, participants completed the NASA-TLX questionnaire in order to explore the cognitive load required by each device. Results showed similarities and differences between each device. Specifically, participants showed a similar proportion of correct trials, while showing different types of errors for each version of Corsi. Such differences were related to path errors, where response sequence contains the correct blocks but pressed in an incorrect order. Analyses showed that SoftCorsi was more sensitive to those kind of errors. With respect to cognitive load, participants reported that CorsiBot elicited larger mental exigency than SoftCorsi. The present work aims make a relevant contribution to research and clinical teams interested in the assessment of spatial working memory. This work contributes theoretically with evidence on the behavior of memory under different processing contexts. In addition, it has practical implications related to diagnostic issues on the identification of individual differences under distinct assessment modes. Finally, the device showed effectiveness in the assessment and record of responses that permitted exporting, analyzing and visualizing the results. Schemes and source codes of the devices are openly available for free use for any interested research group or institution. [ABSTRACT FROM AUTHOR]

Affective computing is a rising interdisciplinary field of research spanning the areas from artificial intelligence, natural language processing to cognitive and social sciences. Potential applications comprise of man–machine interaction, healthcare, entertainment, teaching, marketing and many more. Despite the increasing number of papers published in the domains of affective computing, emotion recognition, and human–computer interaction (HCI), there are still gaps in the comprehensive literature review that covers all relevant studies in a single study, which this review attempts to address. As a result, this study provides a systematic literature review (SLR) on existing modalities (unimodals) for emotion recognition, emotion models, and trends in relevant studies by selecting articles published from January 2010 to June 2021. To ensure the retrieval of all relevant studies, a review protocol is used that includes both automatic and manual searches. Based on the research questions, the final 129 papers are reviewed and relevant information is extracted. This SLR provides future research directions to assist novice researchers and practitioners in more efficiently utilizing affective computing techniques. [ABSTRACT FROM AUTHOR]

The study of how speech is produced, transmitted, and perceived is a critical component in the curriculum of multiple disciplines—linguistics, communication science and disorders, cognitive science, and speech technology all rely on a fundamental understanding of speech science. Pedagogy in speech science across these disciplines has a rich history of experiential learning techniques. Despite being at the forefront of pedagogical innovations, speech science courses have lagged in terms of their representation of cultural and linguistic diversity in the classroom. Many speech scientists understand that linguistic diversity is a part of all human language systems. However, in our experience, relatively few courses involve the purposeful inclusion of multiple language varieties throughout the course across all topics. The goal of this paper is to highlight how to be more inclusive in teaching speech science. [ABSTRACT FROM AUTHOR]

In recent decades, Functionalism has become a standard approach towards philosophy of mind and cognitive science, Functionalism is inspired by computer science and against prior theories about mind. Functionalism takes mind as a processor and body as a provider of raw data for this processor. Mind with the help of mental algorithms translates perceptional data to symbolic representations as concepts of objects and events. According to some philosophers, this leads to problems like the problem of meaning. In this paper, with an analytical approach, Embodiment is proposed as a solution to these problems. According to Embodied Mind, regarding the body as a mere machine is the root of all problems in Functionalism. Embodied mind is consisting of three pars: 1. Perception-Motor system which presents meaningful perception of objects and events to the mind. 2. Conceptualization system which unites information provided by perceptionmotor system. 3. Metaphors, processes in mind, which enable us to think and talk about everyday and mathematical concepts and meta-language. These are processes, mainly unconscious, in mind for understanding concepts. Embodied Mind rejects the idea of body as mere machine and mind as a brain processes. It also rejects symbolic representations as concepts. Concepts are simulators of objects and events, rooting in interaction between body and the world. Human as an Embodied Being exist in the world and interact with it and this is what makes sense of concepts in mind. [ABSTRACT FROM AUTHOR]

Advanced technologies such as drones, intelligent algorithms and androids have grave implications for human existence. With the purpose of exploring their basis for doing so, the paper proposes a framework for investigating the complex relationship between such devices and human practices and language-mediated cognition. Specifically, it centers on the importance of the typically neglected intermediate layer of culture which not only drives both technophobia and philia but also, more fundamentally, connects pre-reflective experience and socio-material practices by placing advanced technologies in the loop. Theoretically, the paper draws on contributions from performativist Science and Technology Studies and Radically Embodied Cognitive Science and pushes new grounds by stressing their compatibility. Yet, it also emphasizes the importance of the enlanguaged side of cognition which is a requirement for human-style socio-material practices and, hence, the emergence of cultures that fetishizes certain technologies. [ABSTRACT FROM AUTHOR]

In this paper I reply to the four critical articles that were provided in response to my book Deconstruction (MIT Press 2021). It proceeds in four steps: (1) I begin with a reply to Stanisław Chankowski’s use of the psychoanalytic term “fetishistic denial” to describe the formal character of the text. (2) I then engage with the criticism supplied by Piotr Kozak, who questions deconstruction’s theory of truth (or its lack thereof). (3) From this, I take-up and respond to Przemysław Nowakowski’s proposal that deconstruction might provide a way to reimagine the interdisciplinarity of cognitive science. And (4) I conclude with a response to Michał Piekarski’s mashup of Ludwig Wittgenstein and Jacques Derrida, which supplies a reading of these two thinkers that is arguably greater than the sum of the parts. The objective of the reply is not to offer a defense of myself or my text but to engage with these interesting and insightful reviews in a way that opens the space for productive dialogue. [ABSTRACT FROM AUTHOR]

Many central creedal statements in Christianity presuppose the existence of a substantial self, even though Christian tradition has not always explicitly used this terminology. However, in contemporary philosophy, the traditional Christian view has been charged with empirical inadequacy, an objection often motivated by neuroscientific considerations. In this paper, I examine the empirical adequacy of the traditional Christian view from a phenomenological perspective and from emerging contemporary cognitive scientific perspectives that downplay or de-emphasize the brain's role in cognition. I argue that neither perspective supports fatal objections to the traditional view and I explain how the traditional Christian view of the self can be synthesized with some novel philosophical developments that suggest the continued relevance of the view. [ABSTRACT FROM AUTHOR]

The terms "extended cognition" and the "extended mind" identify two strands of philosophical argument that are commonly subsumed under the general heading of active externalism. The present paper describes an integrated approach to understanding extended cognition and the extended mind—one that papers over the differences between these two, ostensibly distinct, forms of cognitive extension. As an added bonus, the paper describes how active externalism might be applied to the realm of non-cognitive phenomena, thereby yielding an expansion in the theoretical and empirical scope of the active externalist enterprise. Both these points of progress stem from what is called the dispositional hypothesis. According to the dispositional hypothesis, extended cognition occurs when the mechanisms responsible for the manifestation of dispositional properties include components that lie beyond the borders of the thing to which the dispositional properties are ascribed. • A clearer explication of active externalist theses is required. • According to the dispositional hypothesis, cognitive extension occurs when the mechanisms responsible for the manifestation of dispositional properties extend beyond the borders of the entity to which dispositional properties are ascribed. • A consideration of dispositional properties provides the basis for a unified approach to understanding extended cognition and the extended mind. • Active externalism can be applied to phenomena that do not fall within the empirical orbit of cognitive science. [ABSTRACT FROM AUTHOR]

Three special issues of Entropy journal have been dedicated to the topics of "Information-Processing and Embodied, Embedded, Enactive Cognition". They addressed morphological computing, cognitive agency, and the evolution of cognition. The contributions show the diversity of views present in the research community on the topic of computation and its relation to cognition. This paper is an attempt to elucidate current debates on computation that are central to cognitive science. It is written in the form of a dialog between two authors representing two opposed positions regarding the issue of what computation is and could be, and how it can be related to cognition. Given the different backgrounds of the two researchers, which span physics, philosophy of computing and information, cognitive science, and philosophy, we found the discussions in the form of Socratic dialogue appropriate for this multidisciplinary/cross-disciplinary conceptual analysis. We proceed as follows. First, the proponent (GDC) introduces the info-computational framework as a naturalistic model of embodied, embedded, and enacted cognition. Next, objections are raised by the critic (MM) from the point of view of the new mechanistic approach to explanation. Subsequently, the proponent and the critic provide their replies. The conclusion is that there is a fundamental role for computation, understood as information processing, in the understanding of embodied cognition. [ABSTRACT FROM AUTHOR]

About three decades ago, AI theory underwent a sharp turn as a consequence of criticism that pointed out the problem of externalism in the cognitivist position. Hubert Dreyfus, undoubtedly the main exponent of this criticism, opened the possibility of a Heideggerian reading using the frame problem to bring to light obscurities that otherwise would have been very difficult to detect. However, the question still remains of whether or not Heidegger's philosophy can serve as the source of a positive contribution to AI. In this paper, we argue that in the small measure in which such a task has been attempted, its orientation has been hampered by the omission of what, for Heidegger, was the central issue to be pondered: the question for being and the ontological difference. To propose a possible direction in which AI can be headed as a consequence of this novel perspective, we undertake a brief and schematic review of two published projects suggesting that they both manage to avoid the frame problem and also bear this Heideggerian outlook. [ABSTRACT FROM AUTHOR]

The paper initially develops the semi-Jordan curve theorem on the digital plane with the Marcus-Wyse topology, i.e., M W -topological plane or ( Z 2 , γ) for brevity. We first prove that while every simple closed M W -curve is semi-open in ( Z 2 , γ) , it may not be semi-closed. Given a simple closed M W -curve with l elements, denoted by S C γ l , after establishing a continuous analog of S C γ l denoted by A (S C γ l) , we initially show that A (S C γ l) is both semi-open and semi-closed in ( R 2 , U) , where ( R 2 , U) is the 2 -dimensional real plane R 2 with the usual topology U . Furthermore, we find a condition for A (S C γ l) to separate ( R 2 , U) into exactly two non-empty components, compared to a typical Jordan curve theorem on ( R 2 , U). Since not every S C γ l always separates ( Z 2 , γ) into two nonempty components, we find a condition for S C γ l , l ≠ 4 , to separate ( Z 2 , γ) into exactly two components. The semi-Jordan curve theorem on the M W -topological plane plays an important role in applied topology such as digital topology, mathematical morphology as well as computer science. [ABSTRACT FROM AUTHOR]

Categorical perception (CP) is likely the single finding from speech perception with the biggest impact on cognitive science. However, within speech perception, it is widely known to be an artifact of task demands. CP is empirically defined as a relationship between phoneme identification and discrimination. As discrimination tasks do not appear to require categorization, this was thought to support the claim that listeners perceive speech solely in terms of linguistic categories. However, 50 years of work using discrimination tasks, priming, the visual world paradigm, and event related potentials has rejected the strongest forms of CP and provided little strong evidence for any form of it. This paper reviews the origins and impact of this scientific meme and the work challenging it. It discusses work showing that the encoding of auditory input is largely continuous, not categorical, and describes the modern theoretical synthesis in which listeners preserve fine-grained detail to enable more flexible processing. This synthesis is fundamentally inconsistent with CP. This leads to a different understanding of how to use and interpret the most basic paradigms in speech perception—phoneme identification along a continuum—and has implications for understanding language and hearing disorders, development, and multilingualism. [ABSTRACT FROM AUTHOR]

• Provides a framework combining deep learning with brain-like innate structures. • Introduces time-dependent interactions into Transformer to model emotional coherence. • Embeds a gating mechanism to identify the distinctions of different modalities. Multimodal sentiment analysis and emotion recognition has become an increasingly popular research area, where the biggest challenge is to efficiently fuse the input information from different modality. The recent success is largely credited to the attention-based models, e.g., transformer and its variants. However, the attention-based mechanism often neglects the coherency of human emotion due to its parallel structure. Inspired by the emotional arousal model in cognitive science, a Deep Emotional Arousal Network (DEAN) that is capable of simulating the emotional coherence is proposed in this paper, which incorporates the time dependence into the parallel structure of transformer. The proposed DEAN model consists of three components, i.e., a cross-modal transformer is devised to simulate the functions of perception analysis system of humans; a multimodal BiLSTM system is developed to imitate the cognitive comparator, and a multimodal gating block is introduced to mimic the activation mechanism in human emotional arousal model. We perform extensive comparison and ablation studies on three benchmarks for multimodal sentiment analysis and emotion recognition. The empirical results indicate that DEAN achieves state-of-the-art performance, and useful insights are derived from the results. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of BSS coloring scheme defined in IEEE 802.11ax standard. The efficiency of dense networks for different scenarios was analyzed and compared. This analysis covers various topologies and work configurations through the use of multiple parameters of the PHY and MAC layers. A positive impact of the coloring mechanism on the QoS was observed. The study also analyzed the impact of the RTS/CTS mechanism on the obtained network performance and adequate prioritization of various traffic classes. It was shown that the proper selection of the coloring mechanism parameters in the IEEE 802.11ax standard has a strong impact on QoS and the performance of dense networks. [ABSTRACT FROM AUTHOR]

This paper examines the interplay between integrative explanatory pluralism and the quest for unified theories. We argue that when grounded in virtues associated with satisfactory explanations, integrative pluralism exhibits an inherent instability stemming from the conflict between the demand for unity and the commitment to preserving a patchwork of disparate partial explanations. A case study in cognitive science illuminates the challenges of maintaining both systematicity and depth in explanations within this framework. While this instability does not render integrative pluralism fundamentally flawed, it stresses the importance of a diachronic analysis of scientific dynamics and norms. The conclusion highlights the continued value of integrative pluralism in interdisciplinary research programs, while emphasizing its role as a temporary rather than permanent approach. [ABSTRACT FROM AUTHOR]

This is an opinion paper about the strengths and weaknesses of Deep Nets for vision. They are at the heart of the enormous recent progress in artificial intelligence and are of growing importance in cognitive science and neuroscience. They have had many successes but also have several limitations and there is limited understanding of their inner workings. At present Deep Nets perform very well on specific visual tasks with benchmark datasets but they are much less general purpose, flexible, and adaptive than the human visual system. We argue that Deep Nets in their current form are unlikely to be able to overcome the fundamental problem of computer vision, namely how to deal with the combinatorial explosion, caused by the enormous complexity of natural images, and obtain the rich understanding of visual scenes that the human visual achieves. We argue that this combinatorial explosion takes us into a regime where "big data is not enough" and where we need to rethink our methods for benchmarking performance and evaluating vision algorithms. We stress that, as vision algorithms are increasingly used in real world applications, that performance evaluation is not merely an academic exercise but has important consequences in the real world. It is impractical to review the entire Deep Net literature so we restrict ourselves to a limited range of topics and references which are intended as entry points into the literature. The views expressed in this paper are our own and do not necessarily represent those of anybody else in the computer vision community. [ABSTRACT FROM AUTHOR]

The success of current deep saliency models heavily depends on large amounts of annotated human fixation data to fit the highly non-linear mapping between the stimuli and visual saliency. Such fully supervised data-driven approaches are annotation-intensive and often fail to consider the underlying mechanisms of visual attention. In contrast, in this paper, we introduce a model based on various cognitive theories of visual saliency, which learns visual attention patterns in a weakly supervised manner. Our approach incorporates insights from cognitive science as differentiable submodules, resulting in a unified, end-to-end trainable framework. Specifically, our model encapsulates the following important components motivated from biological vision. (a) As scene semantics are closely related to visually attentive regions, our model encodes discriminative spatial information for scene understanding through spatial visual semantics embedding. (b) To model the objectness factors in visual attention deployment, we incorporate object-level semantics embedding and object relation information. (c) Considering the “winner-take-all” mechanism in visual stimuli processing, we model the competition mechanism among objects with softmax based neural attention. (d) Lastly, a conditional center prior is learned to mimic the spatial distribution bias of visual attention. Furthermore, we propose novel loss functions to utilize supervision cues from image-level semantics, saliency prior knowledge, and self-information compression. Experiments show that our method achieves promising results, and even outperforms many of its fully supervised counterparts. Overall, our weakly supervised saliency method makes an essential step towards reducing the annotation budget of current approaches, as well as providing a more comprehensive understanding of the visual attention mechanism. Our code is available at: https://github.com/ashleylqx/WeakFixation.git. [ABSTRACT FROM AUTHOR]

There are few academics today who actively argue against demonic realism. Much of this is perhaps due to the fact that there are comparably few defenders of such. This has created a vacuum for critics to comfortably object to the existence of demons without sophistication (for it is only in the professional exchange of ideas do bad arguments get weeded out and good arguments gain vitality). Add to this the common perception of demonology as an anti-intellectual superstition and we end up with a threshold for the success of anti-realist arguments to be set quite low. In this paper, I shall survey three of the most familiar objections to demonic realism to arise out of this skeptical intellectual environment: First, and most ambitiously, there is the impossibility of justified belief objection that proffers that belief in demons cannot even in principle be justified no matter how much (scientific) evidence there is. Alternative explanations are always to be preferred. Second, there is the demon-of-the-gaps objection (or category of objections) which insists that demonic realism is hastily posited as a pre-scientific explanation for physical, medical, and psychological mysteries. Third, there is what I call the ethical argument from scapegoating that questions the existence of demons on grounds that, if they in fact exist, such a fact would preclude moral responsibility and the possibility of retributive justice since we could never know if a bad actor was himself morally culpable for his own evils or if he was under the coercive influence of demonic agents. I argue that, despite their rhetorical appeal and kinship with the anti-supernatural sentiments of many academics today, these three arguments are not successful, for these are either based on egregious philosophical assumptions or assumptions about demonology few if any adopt. [ABSTRACT FROM AUTHOR]

Speculative literature is an excellent vehicle for questioning the seemingly natural; faith and the shape of reality are two frequently reflected themes in such works. In The Divine Cities trilogy by Robert Jackson Bennett, the relationships among deities, known as the Divinities; people; and reality are complex and thought provoking. The fictional world hints significantly at our reality when inverting the assumingly top-down relationship between the divine and the mundane. Based on findings from the cognitive sciences and working with the concept of intersubjectivity and interaction theory, this paper explores the enormous role of intersubjective minds in constructing reality in both the fictional and the real world. [ABSTRACT FROM AUTHOR]

Recent advances in the field of cognitive sciences have provided evidence to classify activities with different cognitive engagement levels. High cognitive load and sustained attention may predispose an individual to psychological and physical stress and may result in a lack of performance. Cognitive load monitoring of professionals in high precision fields has gathered significant attention in the current research scenario. The proposed work in continuity has tried to demonstrate the use of two non‐invasive physiological sensing modalities viz. galvanic skin response (GSR) and photoplethysmography (PPG) to elucidate effectiveness in picking up differences of two induced cognitive state categories based on machine learning and statistical methods. This paper demonstrates how GSR and PPG signals data can be effectively utilized to examine the shift in cognitive load. The present work proposes the use of general linear chirplet transform (GLCT) to evaluate the time‐frequency characteristic of GSR and PPG signals and utilize the statistical features in classification. Random Forest, Decision Tree, and k‐Nearest Neighbours demonstrated an accuracy of 92.13%, 88.0%, and 86.13% respectively on a dataset of 20 subjects against an optimized feature set, thus demonstrating the effectiveness of the proposed methodology for differentiating pre‐defined categories of cognitive load. The study shows the potential of GSR and PPG signals attributes and time‐frequency representation using GLCT to monitor cognitive load in real‐life conditions. The proposed work also indicates the possibility to extend the same to attention‐demanding fields such as aviation, medicine, and manufacturing for effective remediation of fatigue periods with increased cognitive demand, which, if sustained, may lead to cognitive decline in the long run. [ABSTRACT FROM AUTHOR]

This paper briefly surveys several prominent modeling approaches to knowledge-based intelligent systems (KBIS) design and, especially, expert systems and the breakthroughs that have most broadened and improved their applications. We argue that the implementation of technology that aims to emulate rudimentary aspects of human intelligence has enhanced KBIS design, but that weaknesses remain that could be addressed with existing research in cognitive science. For example, we propose that systems based on representational plasticity, functional dynamism, domain specificity, creativity, and concept learning, with their theoretical and experimental rigor, can best characterize the problem-solving capabilities of humans and can best overcome five key limitations currently exhibited by knowledge-based intelligent systems. We begin with a brief survey of the relevant work related to KBIS design and then discuss these five shortcomings with new suggestions for how to integrate results from cognitive science to resolve each of them. Our ultimate goal is to increase awareness and direct attention to areas of theoretical and experimental cognitive research that are fundamentally relevant to the goals underlying KBISes. [ABSTRACT FROM AUTHOR]

The critical question for cognitive scientists is what does cognitive science do, if anything, for people? Cognitive science is primarily concerned with human cognition but has fallen short in continuously and critically assessing the who in human cognition. This complacency in a world where white supremacist and patriarchal structures leave cognitive science in the unfortunate position of potentially supporting those structures. We take it that many cognitive scientists operate on the assumption that the study of human cognition is both interesting and important. We want to invoke that importance to note that cognitive scientists must continue to work to show how the field is useful to all of humanity and reflects a humanity that is not white by default. We wonder how much the field has done, and can do, to show that it is useful not only in the sense that we might make connections with researchers in other fields, win grants and write papers, even of the highest quality, but useful in some material way to the billions of non‐cognitive scientists across the globe. [ABSTRACT FROM AUTHOR]

Due to the rapid growth of textual information on the web, analyzing users' opinions about particular products, events or services is now considered a crucial and challenging task that has changed sentiment analysis from an academic endeavor to an essential analytic tool in cognitive science and natural language understanding. Despite the remarkable success of deep learning models for textual sentiment classification, they are still confronted with some limitations. Convolutional neural network is one of the deep learning models that has been excelled at sentiment classification but tends to need a large amount of training data while it considers that all words in a sentence have equal contribution in the polarity of a sentence and its performance is highly dependent on its accompanying hyper-parameters. To overcome these issues, an Attention-Based Convolutional Neural Network with Transfer Learning (ACNN-TL) is proposed in this paper that not only tries to take advantage of both attention mechanism and transfer learning to boost the performance of sentiment classification but also language models, namely Word2Vec and BERT, are used as its the backbone to better express sentence semantics as word vector. We conducted our experiment on widely-studied sentiment classification datasets and according to the empirical results, not only the proposed ACNN-TL achieved comparable or even better classification results but also employing contextual representation and transfer learning yielded remarkable improvement in the classification accuracy. [ABSTRACT FROM AUTHOR]

This paper discusses the resources for deconstruction offered by cognitive science, drawing inspiration from David Gunkel's work on the topic (Deconstruction, MIT Press 2021). The gesture of deconstruction is seen as having a positive impact on the development of this interdisciplinary field by challenging misleading dichotomies and examining its underlying assumptions, such as the symmetry of integration. [ABSTRACT FROM AUTHOR]

The reality of the aesthetic seems to manifest itself more and more in relational and immersive ways that defy analyses that follow the trail of the modern tradition of philosophy, based on the dual gnoseological relationship between subject and object. Even some areas of the new cognitive sciences seem to converge towards a conception of experience as a complex horizon in which variously related vectors operate. From this point of view, it is worth exploring the notion of "field" as a conceptual tool to describe the aesthetic. In this paper we will consider two possible uses of this notion in reference to the aesthetic: to describe experiential modes (following Arnold Berleant), and to describe social dynamics (following Pierre Bourdieu). Yet, the starting point will be some considerations provided by Peter Abbs. We will thus try to show how the notion of "aesthetic field" can be consonant with scientific settings that advocate models of mind that stress its being extended and situated. A particular test bed will be the psychology of art as a discipline spanning philosophical knowledge and empirical investigation. In this key will also be considered the socalled "experiential revolution" in psychology, which indicates an extra-cognitive horizon variously coinciding with the perspective of an aesthetic research focused on the conception of aisthesis as a system of practices of perception, emotion, and expression. According to this conception, the dynamics within the aesthetic field, such as those related to the nexus between perceptual contents and aesthetic properties, or between emotional content and the practices of sensing could prove to be dynamics of "intervenience," rather than of supervenience. [ABSTRACT FROM AUTHOR]

Modern Artificial Intelligence (AI) systems excel at diverse tasks, from image classification to strategy games, even outperforming humans in many of these domains. After making astounding progress in language learning in the recent decade, AI systems, however, seem to approach the ceiling that does not reflect important aspects of human communicative capacities. Unlike human learners, communicative AI systems often fail to systematically generalize to new data, suffer from sample inefficiency, fail to capture common-sense semantic knowledge, and do not translate to real-world communicative situations. Cognitive Science offers several insights on how AI could move forward from this point. This paper aims to: (1) suggest that the dominant cognitively-inspired AI directions, based on nativist and symbolic paradigms, lack necessary substantiation and concreteness to guide progress in modern AI, and (2) articulate an alternative, "grounded", perspective on AI advancement, inspired by Embodied, Embedded, Extended, and Enactive Cognition (4E) research. I review results on 4E research lines in Cognitive Science to distinguish the main aspects of naturalistic learning conditions that play causal roles for human language development. I then use this analysis to propose a list of concrete, implementable components for building "grounded" linguistic intelligence. These components include embodying machines in a perception–action cycle, equipping agents with active exploration mechanisms so they can build their own curriculum, allowing agents to gradually develop motor abilities to promote piecemeal language development, and endowing the agents with adaptive feedback from their physical and social environment. I hope that these ideas can direct AI research towards building machines that develop human-like language abilities through their experiences with the world. [ABSTRACT FROM AUTHOR]