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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]

A central concern of the cognitive science of language since its origins has been the concept of the linguistic system. Recent approaches to the system concept in language point to the exceedingly complex relations that hold between many kinds of interdependent systems, but it can be difficult to know how to proceed when "everything is connected." This paper offers a framework for tackling that challenge by identifying *scale* as a conceptual mooring for the interdisciplinary study of language systems. The paper begins by defining the scale concept--simply, the possibility for a measure to be larger or smaller in different instances of a system, such as a phonemic inventory, a word's frequency value in a corpus, or a speaker population. We review sites of scale difference in and across linguistic subsystems, drawing on findings from linguistic typology, grammatical description, morphosyntactic theory, psycholinguistics, computational corpus work, and social network demography. We consider possible explanations for scaling differences and constraints in language. We then turn to the question of *dependencies between* sites of scale difference in language, reviewing four sample domains of scale dependency: in phonological systems, across levels of grammatical structure (Menzerath's Law), in corpora (Zipf's Law and related issues), and in speaker population size. Finally, we consider the implications of the review, including the utility of a scale framework for generating new questions and inspiring methodological innovations and interdisciplinary collaborations in cognitive-scientific research on language.

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.

The approach that students take in their studies at university is critical not only for their academic success but is equally important in life-long learning for their career and professional development. Heutagogy is the study of self-determined learning and it is important that we appraise how students in higher education are developing their metacognitive awareness in how they learn and study effectively. Cognitive science is an interdisciplinary research area that involves the scientific study of the human mind. It helps provide new knowledge in relation to areas such as memory, problem solving, knowledge transfer and understanding of complex topics. Cognitive science has demonstrated that re-testing oneself on material when learning, enhances and promotes greater retention of knowledge compared to re-reading the material. Learning that is distributed or spaced out over multiple study sessions also allows for greater retention of knowledge in the longer-term compared to 'cramming' of information. To evaluate the use of effective study approaches and habits across three different levels of study in an undergraduate pharmacy programme, a survey study was employed. A paper-based survey was completed by first-, second- and third-year undergraduate pharmacy students (n=192) during class sessions. Although there was some evidence of metacognitive awareness such as using testing (retrieval practice) with practice problems; across all years, suboptimal study approaches such as rereading, copying notes and cramming were endorsed. A schedule of deadlines shaped the organisation of study and time management for most students. Self-testing was predominantly used to test learning rather than an approach used during learning. There was evidence of a difference between the cohorts in relation to decisions for prioritizing studying, returning to review course material and re-reading. The evidence from this study demonstrates that learners would require training on metacognitive awareness and effective study strategies to enable their self-determined learning capabilities to evolve. The linear progression through a programme of study alone will not achieve this. There is a need to embed and emphasize effective strategies for learning into curricula and for faculty to utilise metacognitive awareness in their teaching.

"What is the structure of thought?" is as central a question as any in cognitive science. A classic answer to this question has appealed to a Language of Thought (LoT). We point to emerging research from disparate branches of the field that supports the LoT hypothesis, but also uncovers diversity in LoTs across cognitive systems, stages of development, and species. Our letter formulates open research questions for cognitive science concerning the varieties of rules and representations that underwrite various LoT-based systems and how these variations can help researchers taxonomize cognitive systems., (© 2022 Cognitive Science Society LLC.)

In recent years, a multitude of datasets of human-human conversations has been released for the main purpose of training conversational agents based on data-hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on human behavior and language use. We present a method that leverages the recent development of powerful computational models to obtain the fine-grained annotation required to apply metrics and techniques from Cognitive Science to large datasets. Previous work in Cognitive Science has investigated the question-asking strategies of human participants by employing different variants of the so-called 20-question-game setting and proposing several evaluation methods. In our work, we focus on GuessWhat, a task proposed within the Computer Vision and Natural Language Processing communities that is similar in structure to the 20-question-game setting. Crucially, the GuessWhat dataset contains tens of thousands of dialogues based on real-world images, making it a suitable setting to investigate the question-asking strategies of human players on a large scale and in a natural setting. Our results demonstrate the effectiveness of computational tools to automatically code how the hypothesis space changes throughout the dialogue in complex visual scenes. On the one hand, we confirm findings from previous work on smaller and more controlled settings. On the other hand, our analyses allow us to highlight the presence of "uninformative" questions (in terms of Expected Information Gain) at specific rounds of the dialogue. We hypothesize that these questions fulfill pragmatic constraints that are exploited by human players to solve visual tasks in complex scenes successfully. Our work illustrates a method that brings together efforts and findings from different disciplines to gain a better understanding of human question-asking strategies on large-scale datasets, while at the same time posing new questions about the development of conversational systems.

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.

Several deep learning models are presented: Ref. [[4]] designs a network intrusion detection model, DLNID, that combines an attention mechanism, a bidirectional long short-term memory (LSTM), and an adaptive synthetic sampling, and demonstrates improved performance for severely imbalanced data. In addition, there are a couple of papers on HPO: Ref. [[11]] introduces a greedy I k i -fold cross validation method that vastly reduces the average time required to find the best-performing model with or without a computational budget, and experimentally verifies its improved performance over existing methods. Since its inception as a branch of Artificial Intelligence, Machine Learning (ML) has flourished in recent years. [Extracted from the article]

This document is a response to a comment made by Robertas Damaševičius regarding an article on info-autopoiesis and artificial general intelligence (AGI). The response addresses specific points raised in the comment and clarifies the author's position. It emphasizes that info-autopoiesis, the self-creation of information, is fundamental only to humans and not achievable by artificial creations. The article argues for the impossibility of achieving AGI using info-autopoiesis and suggests that resources should be directed towards more achievable goals in AI. The response also discusses the relationship between biological aspects of human intelligence and AI research, highlighting the use of neural networks and considering the architecture of AGI. It concludes by stating that info-autopoiesis sets a limit to human knowledge based on fundamental principles and that all human creations are syntactic and incapable of semantic interpretation. The text discusses the concept of info-autopoiesis and its application to AI research. Info-autopoiesis is a framework that aims to explain how living organisms function, and the paper explores its potential implications for AI and AGI development. The author acknowledges the limitations of info-autopoiesis and emphasizes the need for interdisciplinary collaboration and ethical considerations in AI research. The text concludes by suggesting areas for further research and expressing gratitude for the comments and suggestions provided by Robertas Damaševičius. [Extracted from the article]

Copyright of TEME: Casopis za Društvene Nauke is the property of TEME: Casopis za Drustvene Nauke and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In EFL learning and teaching processes, mental translation might play an essential role in the mind of the foreign language learner. Some scholarly papers investigate the types of processing in the language learners’ mind such as language perception, language acquisition and dialogue production. Other studies, based on empirical psycholinguistic research about the process of mental translation, investigate mental translation strategies as well as the neuro-linguistic aspects of this process, including cognitive and brain imaging research. There is a consensus among researchers that using neurolinguistics knowledge, one can connect neurological processes in the language learners’ brain with the foreign language learning. This paper tries to contribute to existing studies in this field and highlight the importance of neuro-linguistic research in connection to the biological capacity of the human memory to make connections between language systems in the process of communicative language learning. [ABSTRACT FROM AUTHOR]

To what extent does playing a musical instrument contribute to an individual’s construction of knowledge? This paper aims to address this question by examining music performance from an embodied perspective and offering a narrative-style review of the main literature on the topic. Drawing from both older theoretical frameworks on motor learning and more recent theories on sensorimotor coupling and integration, this paper seeks to challenge and juxtapose established ideas with contemporary views inspired by recent work on embodied cognitive science. By doing so we advocate a centripetal approach to music performance, contrasting the prevalent centrifugal perspective: the sounds produced during performance not only originate from bodily action (centrifugal), but also cyclically return to it (centripetal). This perspective suggests that playing music involves a dynamic integration of both external and internal factors, transcending mere output-oriented actions and revealing music performance as a form of knowledge acquisition based on real-time sensorimotor experience. [ABSTRACT FROM AUTHOR]

Copyright of Trans/Form/Ação is the property of Trans/Form/Acao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Copyright of Studies about Language / Kalbu Studijos is the property of Studies about Language / Kalbu Studijos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Carnap and Popper proposed ways scientists have to work. According to Carnap, they should look for confirmations for hypotheses. In Popper's view, what is important is to try to falsify hypotheses. Cognitive science seems to prove that, in real scientific research, both activities play a role. First, people attempt to confirm hypotheses. Second, they seek examples refuting those hypotheses. This paper is intended to show that the theory of mental models can describe the mental processes involved in both tasks: confirmation and falsification. It addresses the mental possibilities individuals consider in both cases. In addition, the paper reveals that, in accordance with both Carnap's framework and Popper's approach, both mental activities are related to conditional reasoning. [ABSTRACT FROM AUTHOR]

This study utilizes mathematical formalism and Figure-Ground argument mapping to categorize stative locative events in Vietnamese as surjective or bijective. Bijective events exhibit a one-to-one mapping of Figures and Grounds, while surjectives allow a single Figure to map onto multiple Grounds. Through analysis of Vietnamese sentences, the paper demonstrates how bijective and surjective locatives encode deterministic and ambiguous spatial relations between Figures and Grounds, respectively. This novel distinction aids in enhancing the understanding of locative event typologies and provides an explanatory model for cross-linguistic analysis. The proposed integrated formal framework combines predicate logic, set theory, and lexical semantics to account for complex locative meanings, with significant applications in computational and theoretical linguistics, as well as cognitive science. [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]

This paper examines the relationship between societal structures shaped by traditions, norms, laws, and customs, and creative expressions in arts and media through the lens of the predictive coding framework in cognitive science. The article proposes that both dimensions of culture can be viewed as adaptations designed to enhance and train the brain's predictive abilities in the social domain. Traditions, norms, laws, and customs foster shared predictions and expectations among individuals, thereby reducing uncertainty in social environments. On the other hand, arts and media expose us to simulated experiences that explore alternative social realities, allowing the predictive machinery of the brain to hone its skills through exposure to a wider array of potentially relevant social circumstances and scenarios. We first review key principles of predictive coding and active inference, and then explore the rationale of cultural traditions and artistic culture in this perspective. Finally, we draw parallels between institutionalized normative habits that stabilize social worlds and creative and imaginative acts that temporarily subvert established conventions to inject variability. [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]

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]

Purpose: Organizations face a paradox. Because of the disruptions of COVID-19, learning and development was largely put on hold. However, this disruption also changed the value proposition for employees: they expect learning and development to be prioritized. The purpose of this paper is to resolve this paradox by providing a strategic framework that increases the capacity for workplace learning within the constraints of a hybrid world. Design/methodology/approach: Although the COVID-19 disrupted shifted when and where employees learn, it did not change how learning occurs. Therefore, this paper draws from research on workplace learning, cognitive science and neuroscience to develop a conceptual framework of workplace learning and provide practical guidance on how leaders can support it in a hybrid world. Findings: This paper presents a new framework for workplace learning. First, this paper identifies seven key workplace learning behaviors. This paper addresses why a focus on behavior over outcomes is strategically advantageous for hybrid learning. Second, this paper details the opportunities, resources and leadership behaviors that enable each behavior. Research limitations/implications: This paper provides scholars with a new approach to learning and opens avenues for research on the antecedents of workplace learning behaviors, as well as understanding how the behaviors interact over time. Practical implications: This paper helps executives make strategic decisions about hybrid learning based on the science of learning. This paper also provides key tactics for how to encourage and enable employees to learn in remote or hybrid environments. Originality/value: Although there is an abundance of research on individual, team and organizational learning, there is little guidance on what strategies leaders can use to enable learning in the moment, when it is needed most. This paper reorients learning strategy away from learning outcomes to focus on the behaviors that are required to achieve those outcomes. In doing so, this paper provides a model for learning how to learn in a hybrid world. [ABSTRACT FROM AUTHOR]

The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relatively high levels of autonomy. In more unstructured environments, however, the development of fully autonomous mobile robots remains challenging due to the complexity of understanding these environments. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. More recent learning-based methods may replace the complete navigation pipeline or selected stages of the classical approach. For effective deployment, autonomous robots must understand their external environments at a sophisticated level according to their intended applications. Therefore, in addition to robot perception, scene analysis and higher-level scene understanding (e.g., traversable/non-traversable, rough or smooth terrain, etc.) are required for autonomous robot navigation in unstructured outdoor environments. This paper provides a comprehensive review and critical analysis of these methods in the context of their applications to the problems of robot perception and scene understanding in unstructured environments and the related problems of localisation, environment mapping and path planning. State-of-the-art sensor fusion methods and multimodal scene understanding approaches are also discussed and evaluated within this context. The paper concludes with an in-depth discussion regarding the current state of the autonomous ground robot navigation challenge in unstructured outdoor environments and the most promising future research directions to overcome these challenges. [ABSTRACT FROM AUTHOR]

This paper aims to address the divergences and contradictions in the definition of intelligence across different areas of knowledge, particularly in computational intelligence and psychology, where the concept is of significant interest. Despite the differences in motivation and approach, both fields have contributed to the rise of cognitive science. However, the lack of a standardized definition, empirical evidence, or measurement strategy for intelligence is a hindrance to cross-fertilization between these areas, particularly for semantic-based applications. This paper seeks to equalize the definitions of intelligence from the perspectives of computational intelligence and psychology, and offer an overview of themethods used tomeasure intelligence. We argue that there is no consensus for intelligence, and the term is interchangeably used with similar, opposed, or even contradictory definitions in many fields. This paper concludes with a summary of its central considerations and contributions, where we state intelligence is an agent's ability to process external and internal information to find an optimum adaptation (decision-making) to the environment according to its ontology and then decode this information as an output action. [ABSTRACT FROM AUTHOR]

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]

This paper presents a concept for a universal tram driver console that has been developed based on research results regarding the review of tram control panels. These efforts were carried out as part of the project "Innovative training system for tram drivers, based on a full-cab simulator with the application of cognitive science" POIR.01.01.01-00-0135/22, with funding from the Smart Growth Operational Programme. This project involves the development of a tram driver training system based on a full-cabin tram simulator mounted on a motion platform, integrated with eye-tracking technologies and skin conductance response analysis for tram drivers' assessment. The presented research results regarding the development of a universal control panel structure for a tram simulator have led to the creation of a panel based on interchangeable panels. The arrangement of individual switches was determined based on the identification, selection, critical evaluation, and analysis of data from current solutions. [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]

Biological agents can act in ways that express a sensitivity to context-dependent relevance. So far it has proven difficult to engineer this capacity for context-dependent sensitivity to relevance in artificial agents. We give this problem the label the "problem of meaning". The problem of meaning could be circumvented if artificial intelligence researchers were to design agents based on the assumption of the continuity of life and mind. In this paper, we focus on the proposal made by enactive cognitive scientists to design artificial agents that possess sensorimotor autonomy—stable, self-sustaining patterns of sensorimotor interaction that can ground values, norms and goals necessary for encountering a meaningful environment. More specifically, we consider whether the Free Energy Principle (FEP) can provide formal tools for modeling sensorimotor autonomy. There is currently no consensus on how to understand the relationship between enactive cognitive science and the FEP. However, a number of recent papers have argued that the two frameworks are fundamentally incompatible. Some argue that biological systems exhibit historical path-dependent learning that is absent from systems that minimize free energy. Others have argued that a free energy minimizing system would fail to satisfy a key condition for sensorimotor agency referred to as "interactional asymmetry". These critics question the claim we defend in this paper that the FEP can be used to formally model autonomy and adaptivity. We will argue it is too soon to conclude that the two frameworks are incompatible. There are undeniable conceptual differences between the two frameworks but in our view each has something important and necessary to offer. The FEP needs enactive cognitive science for the solution it provides to the problem of meaning. Enactive cognitive science needs the FEP to formally model the properties it argues to be constitutive of agency. Our conclusion will be that active inference models based on the FEP provides a way by which scientists can think about how to address the problems of engineering autonomy and adaptivity in artificial agents in formal terms. In the end engaging more closely with this formalism and its further developments will benefit those working within the enactive framework. [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]

The semantic method of extension and intension presented by Rudolf Carnap may have some problems from the current perspective in cognitive science. For example, that method is strongly linked to logic, and it is hard to determine where its state-descriptions come from, how many they are, and what the relation of accessibility between them is. This paper tries to solve difficulties such as those by updating the method resorting to the theses and results of a contemporary reasoning theory: the theory of mental models. Basically, the update consists of replacing the state-descriptions of the original method with the possibilities of the theory of mental models. That allows reformulating several relevant concepts in Carnap's method in order to better adjust them to the real characteristics of human language. [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]

In this paper we suggest that basic forms of musical entrainment may be considered as intrinsically creative, enabling further creative behaviors which may flourish at different levels and timescales. Rooted in an agent's capacity to form meaningful couplings with their sonic, social, and cultural environment, musical entrainment favors processes of adaptation and exploration, where innovative and functional aspects are cultivated via active, bodily experience. We explore these insights through a theoretical lens that integrates findings from enactive cognitive science and creative cognition research. We center our examination on the realms of groove experience and the communicative and emotional dimensions of music, aiming to present a novel preliminary perspective on musical entrainment, rooted in the fundamental concepts of meaning-making and creativity. To do so, we draw from a suite of approaches that place particular emphasis on the role of situated experience and review a range of recent empirical work on entrainment (in musical and non-musical settings), emphasizing the latter's biological and cognitive foundations. We conclude that musical entrainment may be regarded as a building block for different musical creativities that shape one's musical development, offering a concrete example for how this theory could be empirically tested in the future. [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]

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The progress of EEG-based emotion recognition has received widespread attention from the fields of human-machine interaction and cognitive science. However, recognizing emotions with limited labelled data is still challenging. To address this issue, this paper proposes a self-supervised group meiosis contrastive learning (SGMC) framework for EEG-based emotion recognition. First, to reduce the dependence of emotion labels, SGMC introduces a contrastive learning task according to the alignment of video clips based on the similar EEG response across subjects. Moreover, the model adopts a group projector to extract group-level representations from the group samples to further decrease the subject difference and random effects in EEG signals. Finally, a novel genetics-inspired data augmentation method, named meiosis is developed, which takes advantage of the alignment of video clips among a group of EEG samples to generate augmented groups by pairing, cross exchanging, and separating. The experiments show that SGMC exhibits competitive performance on the publicly available DEAP and SEED datasets. It is worth of noting that the SGMC shows a high ability to recognize emotion even when using limited labelled data. Moreover, the results of feature visualization suggest that the model might have learned video-level emotion-related feature representations to improve emotion recognition. The hyper-parametric analysis further shows the effect of the group size during emotion recognition. Finally, the comparisons of both the symmetric function and the ablation models and the analysis of computational efficiency are carried out to examine the rationality of the SGMC architecture. The code is provided publicly online. [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]

The creditions model is incredibly powerful at explaining both how beliefs are formed and how they influence our perceptions. The model contains several cognitive loops, where beliefs not only influence conscious interpretations of perceptions downstream but are active in the subconscious construction of perceptions out of sensory information upstream. This paper shows how this model is mirrored in the epistemology of two central Buddhist figures, Dignāga (480-540 CE) and Dharmakīrti (c. 550-650 CE). In addition to showing these parallels, the paper also demonstrates that by drawing on Dignāga and Dharmakīrti's theory, we can extend the explanatory power of the creditions model. Namely, while creditions explain how beliefs influence both the conscious interpretation and subconscious construction of sensory information, Dignāga and Dharmakīrti suggest beliefs can even be generative of sensory-like information. I recruit ancient Buddhist texts in conjunction with contemporary cognitive science scholarship to offer a hypothesis for the cognitive mechanisms responsible for this. [ABSTRACT FROM AUTHOR]

Fictionality and fictional experiences are ubiquitous in people's everyday lives in the forms of movies, novels, video games, pretense and role playing, and digital technology use. Despite this ubiquity, though, the field of cognitive science has traditionally been dominated by a focus on the real world. Based on the limited understanding from previous research on questions regarding fictional information and the cognitive processes for distinguishing reality from fiction, we argue for the need for a comprehensive and systematic account that reflects on related phenomena, such as narrative comprehension or imagination embedded into general theories of cognition. This is important as incorporating cognitive processing of fictional events into memory theory reshapes the conceptual map of human memory. In this paper, we highlight future challenges for the cognitive studies of fictionality on conceptual, neurological, and computational levels. Taking on these challenges requires an interdisciplinary approach between fields like developmental psychology, philosophy, and the study of narrative comprehension. Our aim is to build on such interdisciplinarity and provide conclusions on the ways in which new theoretical frameworks of fiction cognition can aid understanding human behaviors in a wide range of aspects of people's daily lives, media consumption habits, and digital encounters. Our account also has the potential to inform technological innovations related to training intelligent digital systems to distinguish fact and fiction in the source material. [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]

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]