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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]

Van Duijn and colleagues propose that minimal cognition can be understood in terms of sensorimotor coordination – that is the coordination between sensory apparatus of an organism and the motor processes that move it around the environment (2006). Despite there being much to recommend this account it still faces some challenges. For example, it does not accord with the intuition that there are cognitive processes that have little to do with sensorimotor coupling, it relies on a strong distinction between metabolic and cognitive processes, and perhaps counterintuitively it denies cognition to plants but grants it to the bacteria on their roots that perform various functions for them. Moreover, it is difficult to see how to account for cognition over the transition from single to multicellular organisms. This paper proposes taking a more radical view of cognition to be what happens in swarms – the coordination of multiple processes through the traces of their actions in the environment. Key to this approach is the observation that the structure of the environment plays an active coordinative role and that this structure results in part from the actions of the system that it helps coordinate. Systems develop sensitivity to the appropriate trace variables in the environment. Viewed as collections of processes bacteria, biofilms, plants, animals can be viewed as cognitive systems in this framework and it has the potential to be applied to the social world. [ABSTRACT FROM AUTHOR]

The computational theory of cognition, or computationalism, holds that cognition is a form of computation. Two issues related to this view are comprised by the goal of this paper: A) Computing systems are traditionally seen as representational systems, but functional and enactive approaches support non-representational theories; B) Recently, a sociocultural theory against computationalism was proposed with the aim of ontologically reducing computing to cognition. We defend, however, that cognition and computation are in action, thus cognition is just a form of computing and that cognition is the explanatory basis for computation. We state that: 1. Representational theories of computing recurring to intentional content run into metaphysical problems. 2. Functional non-representational theories do not incur this metaphysical problem when describing computing in terms of the abstract machine. 3. Functional theories are consistent with enactive in describing computing machines not in a strictly functional way, but especially in terms of their organization. 4. Enactive cognition is consistent with the computationalism in describing Turing machines as functionally and organizationally closed systems. 5. The cognitive explanatory basis for computing improves the computational theory of cognition. When developed in the human linguistic domain, computer science is seen as a product of human socionatural normative practices, however, cognition is just an explanatory, not ontological, basis for computing. The paper concludes by supporting that computation is in action, that cognition is just one form of computing in the world and the explanatory basis for computation. [ABSTRACT FROM AUTHOR]

This Editor's Introduction to the Cognitive Systems Research special issue, "Innovative Dynamical Approaches to Cognitive Systems," has three aims: First, the background and motivation for the topic are stated. Second, overviews of the contributing papers are presented. Third, based on the papers, speculations on future directions in dynamical approaches to the investigation of cognitive systems are presented. Here, the focus is on concepts, data analysis methods, and computational modeling. [ABSTRACT FROM AUTHOR]

As part of cognitive intelligence, concept cognition for knowledge graphs aims to clearly grasp the typical characteristics of the things referred to by the concept, which can provide prior knowledge for machine understanding and thinking. Different from concept learning and formal concept analysis that learn new concepts from data and the general decision rule that comes from an independent decision table, this paper cognizes an existing concept by decision rules that come from multiple granularities. Specifically, 1) concept cognition for knowledge graphs is realized from the perspective of mining multi-granularity decision rule. 2) Decision tables corresponding to four granularities form a multi-granularity decision table group, and then the result from coarser granularity can guide and help obtaining the result from finer granularity. 3) We propose a framework for mining multi-granularity decision rules, which involves going from a multi-granularity decision table group to the frequent maximal attribute patterns to the decision rules to the credible decision rules. Finally, we verified effectiveness of dividing positive and negative data, monotonicity of attribute patterns in a multi-granularity decision table group, and downward monotonicity of credibility, and observed the impact of the parameter min_cov and min_conf on execution times. [ABSTRACT FROM AUTHOR]

Human-extended machine cognition is a specific form of artificial intelligence in which the casually-active physical vehicles of machine-based cognitive states and processes include one or more human agents. Human-extended machine cognition is thus a specific form of extended cognition that sees human agents as constituent parts of the physical fabric that realizes machine-based cognitive capabilities. This idea is important, not just because of its impact on current philosophical debates about the extended character of human cognition, but also because it helps to focus scientific attention on the potential role of the human social environment in realizing novel forms of artificial intelligence. The present paper provides an overview of human-extended machine cognition and situates the concept within the broader theoretical framework of active externalism. The paper additionally shows how the concept of human-extended machine cognition can be applied to existing forms of human–machine interaction, especially those that occur in the context of the contemporary Internet and Web. [ABSTRACT FROM AUTHOR]

This paper discusses the foundations of the theory of socionics, including the rationale behind Aušra Augustinavičiūtė’s model of information processing by the human psyche, and the philosophical thought behind the concept of information metabolism elements. Socionics was developed in the former Soviet Union and may be regarded as analogous to the Myers-Briggs Type Indicator typology of personality. The main goal of this paper is to present socionics to the English-speaking community, in order to better take advantage of its explanatory potential in the fields of interpersonal communication and psychological disorders. Reviewed topics include aspects of Jungian analytical psychology and Kępiński’s information metabolism theory, upon which Augustinavičiūtė based her model. After the model is presented, its theoretical implications are briefly discussed. [ABSTRACT FROM AUTHOR]

The prime focus of scientists and the researchers in the field of intelligent systems is oriented to understand and replicate information processing functionalities of the human brain network. There have been continuous efforts to develop an intelligent knowledge system that incorporates the neuronal processes involved in cognition. In this paper the authors give some details of their unique work on the development of a knowledge system with information processing functionalities moving toward cognitive processing of the human brain, using intelligent links and nodes with processing capabilities. The existing knowledge systems connect only the pieces of information represented by nodes of a network and connect nodes using connectors, referred as edges. The edge is an attribute defining a relationship (e.g. isA, hasA) between the nodes. These edges lack cognitive properties, and the nodes lack functional processing to support efficient information transfer between nodes. The main objective of this paper is to provide an overview of the characteristics of a neurocognitive knowledge network model (NCKM) developed by the authors. NCKM is a knowledge network with nodes and links developed to provide methods that deal with the cognitive processes of the human brain, useful for efficient information processing. These cognitive processes provide self-directivity and learning within the network for intelligent knowledge retrieval. This work opens up a pathway to ingrain cognitive and neuronal characteristics for information processing into knowledge networks. [ABSTRACT FROM AUTHOR]

This review concentrates on the issue of acquisition of abstract words in a cognitive robot with the grounding principle, from relevant theories to practical models of agents and robots. Most cognitive robotics models developed for grounding of language take inspiration from the findings of neuroscience and psychology to get the theoretical skeleton of these models. To better understand these modelling approaches, it is indispensable to work from the base (theoretical accounts) to the top (computational models). Therefore in this paper, succinct definition of abstract words is presented first, and then the symbol grounding issue and accounts of grounded cognition for abstract words are given. The next section discusses the computational modelling approaches for abstract words grounding phenomenon. Finally, important cognitive robotics models are reviewed. This paper also points out the strengths and weaknesses of relevant hypotheses and models for the representation of abstract words in the grounded cognition framework and helps the understanding of issues such as where and why modelling efforts stand to address this problem in comparison with theoretical findings. [ABSTRACT FROM AUTHOR]

Braitenberg vehicles are simple robotic platforms, equipped with rudimentary sensor and motor components. Such vehicles have typically featured as part of thought experiments that are intended to show how complex behaviours are apt to emerge from the interaction of inner control mechanisms with aspects of bodily structure and features of the wider (extra-agential) environment. The present paper describes a framework for creating Braitenberg-like vehicles, which is built on top of a widely used and freely available game engine, namely, the Unity game engine. The framework can be used to study the behaviour of virtual vehicles within a multiplicity of virtual environments. All aspects of the vehicle's design, as well as the wider virtual environment in which the vehicle is situated, can be modified during the design phase, as well as at runtime. The result is a general-purpose simulation capability that is intended to provide the foundation for studies in so-called computational situated cognition —a field of study whose primary objective is to support the computational modelling of cognitive processes associated with the physically-embodied, environmentally-embedded, and materially-extended mind. [ABSTRACT FROM AUTHOR]

The paper presents models describing higher emotions and cognition. It argues that contents of models at the top of the mental hierarchy are higher meanings, which in a simplified way could be called meanings of life. These models are vague-fuzzy and inaccessible to consciousness. Improving these models and making steps toward even tentatively conscious forms of them relates to the highest aesthetic emotions, emotions of the beautiful. Experimental data confirming these relations between the beautiful and higher meanings are presented. [ABSTRACT FROM AUTHOR]

Abstract: Two types of modelling approaches exist to reading an observed person’s emotions: with or without making use of the observing person’s own emotions. This paper focuses on an integrated approach that combines both types of approaches in an adaptive manner. The proposed models were inspired by recent advances in neurological context. Both a neural model and a more abstracted cognitive model are presented. In the first place emotion reading is modelled involving (preparatory) mirroring of body states of the observed person within the observing person. This involves a recursive body loop: a converging positive feedback loop based on reciprocal causation between preparations for body states and emotions felt. Here emotion reading involves the person’s own body states and emotions in reading somebody else’s emotions: first the same feeling is developed by mirroring, and after feeling the emotion, it is imputed to the other person. In the second place, as an extension an adaptive process is modelled based on Hebbian learning of a direct connection between a sensed stimulus concerning another agent’s body state (e.g., face expression) and an emotion imputation state. After this Hebbian learning process the emotion is imputed to the other agent before it is actually felt, or even without it is felt. Both the mirroring and Hebbian learning processes first have been modelled at a neural level, and next, in a more abstracted form at a cognitive level. By means of an interpretation mapping the paper shows the relation between the obtained cognitive model and the neurological model. In addition to specifications of both models and the interpretation mapping, simulation results are shown, and automated verification of relevant emerging properties is discussed. [Copyright &y& Elsevier]

Despite the growing interest in the Internet-of-Things, many organizations remain reluctant to integrating things into their business processes. Different reasons justify this reluctance including things' limited capabilities to act upon the cyber-physical surrounding in which they operate. To address this specific limitation, this paper examines thing empowerment with cognitive capabilities that would make them for instance, selective of the next business processes in which they would participate. The selection is based on things' restrictions like limitedness and goals to achieve like improved reputation. For demonstration purposes, water leaks are used as a case study. A BPEL-based business process driving the fixing of water leaks is implemented involving different cognitive things like moisture sensor. [ABSTRACT FROM AUTHOR]

Abstract Spontaneous pupillary fluctuations are indicative of the cognitive load imposed while doing a task involving memory resources. However, the fluctuations are also dependent on other factors like lighting conditions, uncertainty or the level of confidence while performing the task and so on. This paper aims to separate various components of pupillary response in order to assess the cognitive load and the confidence with which the task is performed. Hybrid decomposition models using ensemble empirical mode decomposition followed by independent component analysis is found to effectively reconstruct the original signal. The variational Mode Decomposition has been used in order to overcome the limitations imposed by empirical mode decomposition. Results show that variational mode decomposition outperforms existing state-of-the-art methods. Further, we attempted to identify the hidden components of pupillary response during cognitive tasks like mental addition and the anagram test. We obtained F score of 0.67 in the detection of cognitive load and F score of 0.99 for the detection of confidence level from the single channel pupil data. [ABSTRACT FROM AUTHOR]

Abstract Categorising is arguably one of the first steps in cognition, because it enables high-level cognitive processing. For a similar reason, categorising is a first step—a preprocessing step—in artificial intelligence, specifically in decision-making, reasoning, and natural language processing. In this paper we categorise the motion of entities. Such categorisations, also known as qualitative representations, represent the preprocessing step for navigation problems with dynamical obstacles. As a central result, we present a general method to generate categorisations of motion based on categorisations of space. We assess its general validity by generating two categorisations of motion from two different spatial categorisations. We show examples of how the categorisations of motion describe and control trajectories. We also establish its soundness in cognitive and mathematical principles. [ABSTRACT FROM AUTHOR]

Abstract: One of the liveliest debates about cognition concerns whether our cognition sometimes extends beyond our brains and bodies. One party says Yes, another No. This paper shows that debate between these parties has been epistemologically confused and requires reorienting. Both parties frequently appeal to empirical considerations and to extra-empirical theoretical virtues to support claims about where cognition is. These things should constrain their claims, but cannot do all the work hoped. This is because of the overlooked fact, uncovered in this paper, that we could never distinguish the rival views empirically or by typical theoretical virtues. I show this by drawing on recent work on testing, predictive accuracy, and theoretical virtues. The recommendation to emerge is that we step back from debate about where cognition is, to the epistemology of what cognition is. [ABSTRACT FROM AUTHOR]

Abstract: This paper discusses an analysis of how scientists select relevant publications, and an application that can assist scientists in this information selection task. The application, called the Personal Publication Assistant, is based on the assumption that successful information selection is driven by recognizing familiar terms. To adapt itself to a researcher’s interests, the system takes into account what words have been used in a particular researcher’s abstracts, and when these words have been used. The user model underlying the Personal Publication Assistant is based on a rational analysis of memory, and takes the form of a model of declarative memory as developed for the cognitive architecture ACT-R. We discuss an experiment testing the assumptions of this model and present a user study that validates the implementation of the Personal Publication Assistant. The user study shows that the Personal Publication Assistant can successfully make an initial selection of relevant papers from a large collection of scientific literature. [Copyright &y& Elsevier]

Abstract: Phenomenal consciousness and social cognition are interlocking capacities, but the relations between them have yet to be systematically investigated. In this paper, I begin to develop a theoretical and empirical framework for such an investigation. I begin by describing the phenomenon known as social pain: the affect associated with the perception of actual or potential damage to one’s interpersonal relations. I then adduce a related phenomenon known as affective contagion: the tendency for emotions, moods, and other affective states to spread from person to person in social contexts. Experimental studies of these two phenomena suggest that affective consciousness depends on perception of the social world in much the same way that it depends on perception of the body – in short, that consciousness is ‘socially embodied’. In the second part of the paper I argue that the distinctive sociality of our species, especially its moral dimension, rests heavily on our ability to represent the conscious states of others. In closing, I put these ideas together and show how they point to a circular causal-mechanistic nexus between consciousness and social mindedness. [Copyright &y& Elsevier]

Abstract: This paper describes how meta-cognitive processes (i.e., the self monitoring and regulating of cognitive processes) may be captured within a cognitive architecture Clarion. Some currently popular cognitive architectures lack sufficiently complex built-in meta-cognitive mechanisms. However, a sufficiently complex meta-cognitive mechanism is important, in that it is an essential part of cognition and without it, human cognition may not function properly. We contend that such a meta-cognitive mechanism should be an integral part of a cognitive architecture. Thus, such a mechanism has been developed within the Clarion cognitive architecture. The paper demonstrates how human data of two meta-cognitive experiments are simulated using Clarion. The simulations show that the meta-cognitive processes represented by the experimental data (and beyond) can be adequately captured within the Clarion framework. [Copyright &y& Elsevier]

For cognitive systems, embodiment appears to be of crucial importance. Unfortunately, nobody seems to be able to define embodiment in a way that would prevent it from also covering its trivial interpretations such as mere situatedness in complex environments. The paper focuses on the definition of embodiment, especially whether physical embodiment is necessary and/or sufficient for cognitive systems. Cognition is characterized as a continuous complex process rather than ahistorical logical capability. Furthermore, the paper investigates the relationship between cognitive embodiment and the issues of understanding, representation and task specification. [Copyright &y& Elsevier]

The aim of this paper was to present a method to enable the analysis of the process of categorization of patients’ testimonials and the comparison of individual categories created by professionals. A complex diagnostic task (case conceptualization) was employed to study the categorization function in professional thinking. Two groups of psychotherapists (30 people in each group) served as subjects of the research. The main objective of the study was to find an appropriate representation of concept maps enabling a comparison of both the categories and the structures between experts. In the comparison process, only the information about the premises justifying each given category was taken into account and represented by a concept-testimonials matrix. Three different elements weighting schemes and matrix factorization-based unsupervised clustering methods were analyzed in the context of consistency and ability to establish main semantic groups of concepts common to the majority of experts. Moreover, special attention was paid to determining the number of main semantic classes. The study showed that even the used representation was similar to the task of documents indexing there was some discrepancy. The highest accuracy in generating main semantic groups was achieved using the PCA and K-Means ( nKM ) (the average false positive rate in clusters was 32%). This method outperformed Tempered PLSA (the average false positive rate per cluster was 52%). It was demonstrated that in analyzed task the nKM method allowed comparing the similarity of concepts even when they were created by various experts using different conceptual apparatus. [ABSTRACT FROM AUTHOR]

Traditionally, models of macro-political change, like those of macro-economics, have been based on extremely unrealistic assumptions about human cognition, ranging from fully informed and rational to completely random. Following from the work of Herbert Simon and contemporaries, a new tradition has developed based on more realistic ideas of human cognition. This paper lays out the need for such models in understanding endogenously produced disjointed change in public policies. It documents the commonality of such changes at the macro-level and points to the contributions of many recent works in developing realistic models of human cognition providing the basis of a new and more fruitful literature. [ABSTRACT FROM AUTHOR]

Science that needs logical demonstration has failed to eliminate religious concepts. It is as if they have own validity that cannot be broken by scientific knowledge we trust the most at present. In this paper, I will attempt to establish a new cognitive theory to help explain the basis of belief in religious concepts. This form of cognition will be named simply unifying-induction or unifying-inductive cognition. As illustrations, I will consider some typical religious discourses involving concepts such as “all-in-one” or “one is everything.” It is these typically religious discourses that science has not been able to easily sweep away by its logical scientific proofs. In the end, although we perhaps cannot know if the religious beings such as gods really exist or not, we may understand these concepts are very the creation of human cognition. It also has important implications for other disciplines such as robotics, developmental psychology, cognitive archaeology, the history of science, the study of religion and so on. [ABSTRACT FROM AUTHOR]

This paper surveys value systems for developmental cognitive robotics. A value system permits a biological brain to increase the likelihood of neural responses to selected external phenomena. Many machine learning algorithms capture the essence of this learning process. However, computational value systems aim not only to support learning, but also autonomous attention focus to direct learning. This combination of unsupervised attention focus and learning aims to address the grand challenge of autonomous mental development for machines. This survey examines existing value systems for developmental cognitive robotics in this context. We examine the definitions of value used—including recent pioneering work in intrinsic motivation as value—as well as initialisation strategies for innate values, update strategies for acquired value and the data structures used for storing value. We examine the extent to which existing value systems support attention focus, learning and prediction in an unsupervised setting. The types of robots and applications in which these value systems are used are also examined, as well as the ways that these applications are evaluated. Finally, we study the strengths and limitations of current value systems for developmental cognitive robots and conclude with a set of research challenges for this field. [ABSTRACT FROM AUTHOR]

Traditional approaches model consciousness as the outcome either of internal computational processes or of cognitive structures. We advance an alternative hypothesis – consciousness is the hallmark of a fundamental way to organise causal interactions between an agent and its environment. Thus consciousness is not a special property or an addition to the cognitive processes, but rather the way in which the causal structure of the body of the agent is causally entangled with a world of physical causes. The advantage of this hypothesis is that it suggests how to exploit causal coupling to envisage tentative guidelines for designing conscious artificial agents. In this paper, we outline the key characteristics of these causal building blocks and then a set of standard technologies that may take advantage of such an approach. Consciousness is modelled as a kind of cognitive middle ground and experience is not an internal by-product of cognitive processes but the external world that is carved out by means of causal interaction. Thus, consciousness is not the penthouse on top of a 50 stores cognitive skyscraper, but the way in which the steel girders snap together from bottom to top. [ABSTRACT FROM AUTHOR]

This paper studies the role of cognition and affect in decision-making as well as notions of Type 1 and 2 processes and behaviors typically used in dual process theories. In order to demonstrate that there is no 1:1 correspondence between types of observed behavior and internal processes causing them, and that Type 1 and Type 2 processes can be produced by a single system, we implemented a computational model integrating affective and cognitive processing. Our model is based on the model of Marinier, Laird, and Lewis (2009). We modified it by increasing the agent’s visual field, adding a GOFAI-style cognitive module (sub-goal management) and expanding the environment by a high-threat tile, to which the agent responds with a hard-wired automatic reaction. This allowed us to generate and observe different types of behavior and study interesting interactions between cognitive and affective control. By comparing our re-implementation to the modified agent, we demonstrated clear cases of Type 1 (fast, automatic) and Type 2 (slow, deliberative) behavior, providing further evidence for the “single-system, two processes” hypothesis. [ABSTRACT FROM AUTHOR]

There is a long history of implementing internal simulation mechanisms in robotics, typically for the purpose of predicting the outcomes of motor commands before executing them. In the literature on human cognition, however, the relevance of such mechanisms goes beyond that of prediction: they also provide foundational aspects of social cognition and interaction. In this paper, we present a review of internal simulation mechanisms from this perspective. We contrast the roles they play in human cognition, in particular in the context of social interaction, with robotic implementations. We further discuss work in social robotics, emphasising in particular that a substantial effort currently goes into evaluating social robot systems, but that social robots to date are still limited in their abilities. We further discuss episodic simulations, which are functionally distinct from the type of internal simulations we consider here, and note their role in prospective thought in particular. Overall, we conclude that one of the necessary next steps on the road to social robots may be to develop social abilities from the bottom up using internal simulations. By reviewing how these aspects all tie together in human cognition, we hope to clarify how this may be achieved. [ABSTRACT FROM AUTHOR]

In cognitive science, image schemas are identified as fundamental patterns of cognition. They are schematic prelinguistic conceptualisations of events and serve as conceptual building blocks for concepts. This paper proposes that image schemas can play an important role in computational concept invention, namely within the computational realisation of conceptual blending. We propose to build a library of formalised image schemas, and illustrate how they can guide the search for a base space in the concept invention work flow. Their schematic nature is captured by the idea of organising image schemas into families. Formally, they are represented as heterogeneous, interlinked theories. [ABSTRACT FROM AUTHOR]

The concept of stigmergy, a mechanism for the coordination of actions via the trace they leave in a medium, can explain self-organizing activities in a broad range of domains, including social insects, collaborative websites, and human institutions. The present paper attempts to bring some order to these diverse applications by classifying varieties of stigmergy according to general aspects: the number of agents involved, the relative persistence or transience of the trace, the use of sematectonic or marker-based traces, and the quantitative or qualitative characteristics of traces. The resulting cases are essentially continuous, as more complex cases can be understood as having evolved out of simpler ones. One application is cognition, which can be viewed as an interiorization of the individual stigmergy that helps an agent to perform a complex project by registering the state of the work in the trace, thus providing an external memory. Another application is the evolution of cooperation, in which agents learn to profit from the synergy produced by the spontaneous stigmergic coordination between their initially independent actions, thus bypassing the problem of “free riders” that exploit the cooperators’ efforts. [ABSTRACT FROM AUTHOR]

Ontologies are explicit specifications of concepts and their relationships. In the context of a semantic web of independently developed ontologies, overcoming interoperability and heterogeneity issues is of considerable importance. Many semantic web applications, such as matching of instances in social networks, reasoning over combined knowledge bases, and knowledge sharing among services, rely on ontology alignment. While existing research in this area has developed a wide range of different heuristics, in this paper we propose to look towards cognitive science, specifically analogical reasoning, to support ontology alignment. We investigate the question whether ontology alignment is rooted in the same cognitive process as analogical reasoning. We apply the LISA system, a cognitively-based model of human analogical reasoning, to ontology alignment and present a comprehensive experimental study to determine its performance on ontology alignment problems. [ABSTRACT FROM AUTHOR]

Abstract: In the “Socially Extended Mind,” Shaun Gallagher further develops the theory, introduced in “Mental Institutions” (Gallagher & Crisafi, 2009), that social institutions can become part of a cognitive system. Building on first wave theories of the extended mind, Gallagher (2013) argues that just as our minds are capable of coupling with artifacts in the environment to form larger cognitive systems, our minds are also capable of coupling with social institutions. In this paper we argue that whether extending cognition in this way is fruitful comes down to the details. Systems are incredibly complex, and must be addressed at the local level where components concretely link up. Only after such work is done can we confidently claim that something as abstract as the “legal system” constitutes the mind. [Copyright &y& Elsevier]

Abstract: In his paper “Socially Extended Mind,” Shaun Gallagher aims to broaden the perspective of the philosophy of cognitive science and to bring theoretical discussions to new grounds. However, I argue that such comprehensive attempt needs to be worked out and underpinned in more detail. I start by sketching the theoretical landscape, and continue by pointing out some ambiguities that are in need of further clarification. In the last part, I introduce a distinction between global and local frames of cognition and argue that the idea of a local frame can contribute to critical inquiry. [Copyright &y& Elsevier]

Abstract: This paper contrasts conservative and liberal interpretations of the extended mind hypothesis. The liberal view, defended here, considers cognition to be socially extensive, in a way that goes beyond the typical examples (involving notebooks and various technologies) rehearsed in the extended mind literature, and in a way that takes cognition to involve enactive processes (e.g., social affordances), rather than functional supervenience relations. The socially extended mind is in some cases constituted not only in social interactions with others, but also in ways that involve institutional structures, norms, and practices. Some of the common objections to the extended mind are considered in relation to this liberal interpretation. Implications for critical social theory are explored. [Copyright &y& Elsevier]

Abstract: In two recent papers, Shaun Gallagher asks the question of how we interact with institutions. To answer it, he proposes to expand Clark and Chalmers’ extended mind hypothesis into the societal realm. He introduces the idea of the socially extended mind, to reflect the fact that social institutions can help us to perform cognitive tasks that we would not be able to do without them. Drawing on work by Carol Gilligan, I argue that the socially extended mind view is limited to addressing patriarchal, rule-based, hierarchical institutions and interactions, and unable to grasp democratic, fluid and horizontal aspects of society. Gallagher is sensitive to a similar worry and suggests a combination of the socially extended mind and enactive ideas. At first sight, it might seem as if enaction would be the ideal candidate to address the democratic aspects of society, and so the two would be good bed fellows. But I argue that this is unlikely, due to the incompatibilities between enaction and the extended mind. I claim instead that the enactive approach to intersubjectivity—participatory sense-making—can capture both patriarchic and democratic aspects of society. Patriarchy and democracy can be seen as lying on the spectrum of participation, which ranges from orientational sense-making to joint sense-making. Enaction investigates the relations along the whole spectrum and how they play out in actual social interactions, also with institutions. [Copyright &y& Elsevier]

Abstract: Cognitive systems research has predominantly been guided by the historical distinction between emotion and cognition, and has focused its efforts on modelling the “cognitive” aspects of behaviour. While this initially meant modelling only the control system of cognitive creatures, with the advent of “embodied” cognitive science this expanded to also modelling the interactions between the control system and the external environment. What did not seem to change with this embodiment revolution, however, was the attitude towards affect and emotion in cognitive science. This paper argues that cognitive systems research is now beginning to integrate these aspects of natural cognitive systems into cognitive science proper, not in virtue of traditional “embodied cognitive science”, which focuses predominantly on the body’s gross morphology, but rather in virtue of research into the interoceptive, organismic basis of natural cognitive systems. [Copyright &y& Elsevier]

Abstract: This paper proposes a model and theory of leadership emergence whereby (1) small social groups are modeled as small world networks and a betweeness metric is shown to be a property of networks with strong leadership, and (2) a theory of group formation based on stigmergy explains how such networks evolve and form. Specifically, dominant actors are observed to emerge from simulations of artificial termites constructing a wood chip network in a random walk, suggesting a correlation between various preferential attachment rules and emergent network topologies. Three attachment rules are studied: maximizing node betweeness (intermediary power), maximizing node degree (node connectivity), and limiting radius (size of the network in terms of network distance). The simulation results suggest that a preference for maximizing betweeness produces networks with structure similar to the 62-node 9-11 terrorist network. Further simulations of emergent networks with small world properties (small radius) and high betweeness centrality (strong leader) are shown to match the topological structure of the 9-11 terrorist network, also. Interestingly, the same properties are not found in a small sampling of human made physical infrastructure networks such as power grids, transportation systems, water and pipeline networks, suggesting a difference between social network emergence and physical infrastructure emergence. Additionally, a contagion model is applied to random and structured networks to understand the dynamics of anti-leader sentiment (uprisings and counter-movements that challenge the status quo). For random networks, simulated pro-leader (pro-government) and anti-leader (pro-rebel) sentiments are propagated throughout a social network like opposing diseases to determine which sentiment eventually prevails. Simulations of the rise of rebel sentiment versus the ratio of rebel to government sentiment show that rebel sentiment rises on less than 100% rebel/government sentiment when government sentiment is high (strong leadership), but requires greater than 100% rebel/government sentiment when government sentiment is low (weak leadership). However, when applied to the structured 9-11 terrorist network, rebel sentiment is slow to rise against strong leadership, because of the high betweeness structure of the 9-11 network. These results suggest a theory of how and why human stigmergy evolves networks with strong leaders, and why successful social networks are resilient against anti-leader sentiment. The author concludes that a combination of small world and high betweeness structure explain how social networks emerge strong leadership structure and why the resulting networks are resilient against being overthrown by a dissenting majority. [Copyright &y& Elsevier]

Abstract: The information processing paradigm advocated by integrate four functions – affect, motivation, cognition, and behavior – into three levels – reactive, routine, and reflective. However, it does not contain details of implementation. The three levels of information processing paradigm ties well with our view of two sources for inputs (or stimuli), namely external and internal inputs. This article provides an agent-based implementation of the three levels of information processing and clarifies the information flows of affect, motivation, cognition, behavior as well as perception. We simulate the three levels of information processing in a predator–prey environment. This paper shows manners in which affect, motivation, cognition, and behavior can be represented and used by agents at different levels of processing. This study contributes to understanding and processing of emotions, to three levels of information processing, and to predator–prey simulation. [Copyright &y& Elsevier]

Abstract: Any non-trivial task requires an appropriate representational formalism. Usually, for single-task or single-domain problems this choice of formalism is not explicitly made by the agent itself, but by the agent designer, and is implicit in the choice of data structures and algorithms used by the agent. However, complex cognition involves domains where the type of problems that the agent is expected to solve is not clear at the outset. Instead, at each stage of the problem solving process, the agent is expected to choose an appropriate formalism, solve the problem and integrate these results over the course of the entire problem solving episode. In this paper, we present one approach to solving two of the above problems – how does an agent choose the right representation and how can it integrate results from multiple representations over the course of problem solving? We present this approach in the context of Polyscheme, a cognitive architecture that is strongly integrated, focused on inference and adaptive to new information. We describe the representational formalisms and associated processes present in Polyscheme (propositional and spatial) and the decision cycle that allows information from multiple representations to be integrated. Using examples from complex tasks such as constraint satisfaction, language understanding and planning, we show how a Polyscheme agent can show improved performance by leveraging its multiple representations without the hindsight of representational choice. [Copyright &y& Elsevier]

Abstract: Goals play an important role in human cognition. Different aspects of human mind influence the generation of goals they pursue, and the goals guide their behaviors. In psychology, researchers made significant efforts to study goals and their origin, and cognitive architectures include various facilities to handle goals of artificial agents. One such architecture, Icarus, supports goal-driven behaviors while maintaining reactivity, and the top-level goals play the role of guiding Icarus agents’ behaviors. However, the architecture covers neither the origin of its top-level goals nor the management of them, and this imposes various restrictions on Icarus, like the limited autonomy. In this paper, we extend the architecture to provide the capability to nominate top-level goals using the notion of long-term, general goals, and manage the nominated goals by prioritizing them. For prioritization of goals, we introduce a novel capability to match concepts in a continuous manner. We show some illustrative examples in an urban driving domain, and discuss related and future work in this direction before we conclude. [Copyright &y& Elsevier]

Abstract: Deductive reasoning is an essential part of complex cognition. It occurs whenever human beings (or machines) draw conclusions that go beyond what is explicitly provided. Reasoning about spatial relations is an excellent testbed for the assessment of competing reasoning theories. In the present paper we show that such competing theories are often less diverse than one might think. We introduce an approach for how relational reasoning can be conceived as verbal reasoning. We describe a theory of how humans construct a one-dimensional mental representation given spatial relations. In this construction process objects are inserted in a dynamic structure called a “queue” which provides an implicit direction. The spatial interpretation of this direction can theoretically be chosen freely. This implies that choices in the process of constructing a mental representation influence the result of deductive spatial reasoning. To derive the precise rules for the construction process we employ the assumption that humans try to minimize their cognitive effort, and two cost measures are compared to judge the efficiency of the construction process. From this we deduce how the queue should be constructed. We discuss empirical evidence for this approach and provide algorithms for a computational implementation of the construction and reasoning process. [Copyright &y& Elsevier]

Abstract: The sensorimotor theory () discusses a special instance of lack of perceptual experience despite no sensory impairment. The phenomenon dubbed “experiential blindness” is cited as evidence for a constitutive relation between sensorimotor skills and perceptual experience. Recently it has been objected () that the cases described by Noë as experiential blindness are cases of pure sensory deficit. This paper argues that while the objections bring out limitations of Noë’s sensorimotor theory they do not do enough to challenge a robust perception–action interdependence claim. There are genuine cases of experiential blindness and these are better explained by the hypothesis of the interdependence of perception and action rather than by a passive vision approach. The cases provide support for a strong thesis of embodied cognition where ongoing sensorimotor dynamics non-trivially constrain perceptual content. [ABSTRACT FROM AUTHOR]

Abstract: The hypothesis of extended cognition maintains that cognitive processes sometimes span the brain, body, and world. One of the most prominent types of arguments for this hypothesis begins with observations of the role of certain sorts of bodily and environmental influences on cognitive processes, then concludes that these bodily and environmental influences are themselves cognitive processes. This paper will argue that, while it is widely appreciated that the simplest versions of these “coupling arguments” are fallacious, the advocates of extended cognition still seem to underestimate how prevalent even the simplest forms are in the literature, why they are so pervasive, and how these fallacious arguments might be avoided by greater attention to a plausible theory of what distinguishes cognitive processes from non-cognitive processes. [ABSTRACT FROM AUTHOR]

Abstract: This paper explores the relationship between several ideas about the mind and cognition. The hypothesis of extended cognition claims that cognitive processes can and do extend outside the head, that elements of the world around us can actually become parts of our cognitive systems. It has recently been suggested that the hypothesis of extended cognition is entailed by one of the foremost philosophical positions on the nature of the mind: functionalism, the thesis that mental states are defined by their functional relations rather than by their physical constituents. Furthermore, it has been claimed that functionalism entails a version of extended cognition which is sufficiently radical as to be obviously false. I survey the debate and propose several ways of avoiding this conclusion, emphasizing the importance of distinguishing the hypothesis of extended cognition from the related notion of the extended mind. [ABSTRACT FROM AUTHOR]

Abstract: Computational concepts of cognition, their implementation in complex autonomous systems, and their empirical evaluation are key techniques to understand and validate concepts of cognition and intelligence. In this paper we want to describe computational concepts of cognition that were successfully implemented in the domain of soccer playing robots and show the interactions between cognitive concepts, software engineering and real-time application development. Beside a description of the general concepts we will focus on aspects of perception, behavior architecture, and reinforcement learning. [Copyright &y& Elsevier]

Abstract: One of the fundamental human cognitive processes is problem solving. As a higher-layer cognitive process, problem solving interacts with many other cognitive processes such as abstraction, searching, learning, decision making, inference, analysis, and synthesis on the basis of internal knowledge representation by the object–attribute-relation (OAR) model. Problem solving is a cognitive process of the brain that searches a solution for a given problem or finds a path to reach a given goal. When a problem object is identified, problem solving can be perceived as a search process in the memory space for finding a relationship between a set of solution goals and a set of alternative paths. This paper presents both a cognitive model and a mathematical model of the problem solving process. The cognitive structures of the brain and the mechanisms of internal knowledge representation behind the cognitive process of problem solving are explained. The cognitive process is formally described using real-time process algebra (RTPA) and concept algebra. This work is a part of the cognitive computing project that designed to reveal and simulate the fundamental mechanisms and processes of the brain according to Wang’s layered reference model of the brain (LRMB), which is expected to lead to the development of future generation methodologies for cognitive computing and novel cognitive computers that are capable of think, learn, and perceive. [Copyright &y& Elsevier]

Abstract: In the paper, we present a multi-aspect data analysis approach for investigating human computation mechanism. Multi-aspect analysis in multiple human brain data sources is an important methodology in Brain Informatics, which emphasizes on a systematic way for investigating human information processing mechanisms, including measuring, collecting, modeling, transforming, managing, and mining multiple human brain data obtained from various cognitive experiments by using powerful equipments, such as fMRI and EEG. After giving an outline of Brain Informatics methodology, we describe how to design cognitive experiments of mental arithmetic task with multiple difficulty levels for obtaining multiple EEG and fMRI data sources, and how to analyze such data for investigating the spatiotemporal characteristics and flow of human computation processing. Such an investigation can be regarded as a case study using Brain Informatics methodology. Experimental results show the usefulness of our approach. [Copyright &y& Elsevier]

Abstract: Analogy making is a central construct in human cognition and plays an important role to explain cognitive abilities. While various psychologically or neurally inspired theories for analogical reasoning have been proposed, there is a lack of a logical foundation for analogical reasoning in artificial intelligence and cognitive science. We aim to close this gap and propose heuristic-driven theory projection (HDTP), a mathematically sound framework for analogy making. HDTP represents knowledge about the source and the target domain as first-order logic theories and compares them for structural commonalities using anti-unification. The paper provides an overview of the syntactic principles of HDTP, explains all phases of analogy making at a formal level, and illustrates these phases with examples. [Copyright &y& Elsevier]

Abstract: In this paper, we present an approach to transfer that involves analogical mapping of symbols across different domains. We relate this mechanism to Icarus, a theory of the human cognitive architecture. Our system can transfer skills across domains hypothesizing maps between representations, improving performance in novel domains. Unlike previous approaches to analogical transfer, our method uses an explanatory analysis that compares how well a new domain theory explains previous solutions under different mapping hypotheses. We present experimental evidence that the new mechanism improves transfer over Icarus’ basic learning processes. Moreover, we argue that the same features which distinguish Icarus from other architectures support representation mapping in a natural way and operate synergistically with it. These features enable our analogy system to translate a map among concepts into a map between skills, and to support transfer even if two domains are only partially analogous. We also discuss our system’s relation to other work on analogy and outline directions for future research. [Copyright &y& Elsevier]

Abstract: Existing models that integrate emotion and cognition generally do not fully specify why cognition needs emotion and conversely why emotion needs cognition. In this paper, we present a unified computational model that combines an abstract cognitive theory of behavior control (PEACTIDM) and a detailed theory of emotion (based on an appraisal theory), integrated in a theory of cognitive architecture (Soar). The theory of cognitive control specifies a set of required computational functions and their abstract inputs and outputs, while the appraisal theory specifies in more detail the nature of these inputs and outputs and an ontology for their representation. We argue that there is a surprising functional symbiosis between these two independently motivated theories that leads to a deeper theoretical integration than has been previously obtained in other computational treatments of cognition and emotion. We use an implemented model in Soar to test the feasibility of the resulting integrated theory, and explore its implications and predictive power in several task domains. [Copyright &y& Elsevier]

Abstract: At what stage in the emotion process do people apprehend the relational meaning of their encounters with the practical or social environment? For many appraisal theorists, meaning (usually or always) comes first, shaping the activation of functional response modes by top-down influence. For transactional theorists, meaning emerges bottom-up in parallel with the real-time consolidation of the response syndrome. For attribution theorists, meaning is applied to emotional episodes after the fact, and is not an intrinsic part of any emotion-generative mechanisms. For communicative theorists, emotions are flexible strategies for conveying meanings to others. This paper reviews arguments and evidence for and against these four approaches and attempts to integrate their insights by sketching out a view of emotions as functional modes of engagement with the practical and social environment (relation alignment), whose operation is transformed by the imposition of societal prescriptions and descriptions. From this perspective, relational meaning is often implicated in the causes, content, and consequences of emotion but its roles in these phases of the transaction do not always coincide. Further, emotions should not be modelled simply as determinate responses to separately defined meanings or as communicative acts driven by internal goals, but also as situated adjustments to unfolding events and as active ways of transforming or producing meaning in collaboration with other people. [Copyright &y& Elsevier]