Cognitive systems

During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [35]) adopt a classical symbolic approach, some (e.g. LEABRA[48]) are based on a purely con-nectionist model, while others (e.g. CLARION [59]) adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and reasoning are also available [34]. In this paper we propose a reflection on the role that Conceptual Spaces, a framework developed by Peter Gärdenfors [24] more than fifteen years ago, can play in the current development of the Knowledge Level in Cognitive Systems and Architectures. In particular, we claim that Conceptual Spaces offer a lingua franca that allows to unify and generalize many aspects of the symbolic, sub-symbolic and diagrammatic approaches (by overcoming some of their typical problems) and to integrate them on a common ground. In doing so we extend and detail some of the arguments explored by Gärdenfors [23] for defending the need of a conceptual, intermediate, representation level between the symbolic and the sub-symbolic one. In particular we focus on the advantages offered by Conceptual Spaces (w.r.t. symbolic and sub-symbolic approaches) in dealing with the problem of compositionality of representations based on typicality traits. Additionally, we argue that Conceptual Spaces could offer a unifying framework for interpreting many kinds of diagrammatic and analogical representations. As a consequence, their adoption could also favor the integration of diagrammatical representation and reasoning in CAs.

Based on a survey of behavioral finance literature, this paper presents a descriptive model of individual investor behavior in which investment decisions are seen as an iterative process of interactions between the investor and the investment environment. This investment process is influenced by a number of interdependent variables and driven by dual mental systems, the interplay of which contributes to boundedly rational behavior where investors use various heuristics and may exhibit behavioral biases. In the modeling tradition of cognitive science and intelligent systems, the investor is seen as a learning, adapting, and evolving entity that perceives the environment, processes information, acts upon it, and updates his or her internal states. This conceptual model can be used to build stylized representations of (classes of) individual investors, and further studied using the paradigm of agent-based artificial financial markets. By allowing us to implement individual investor behavior, to choose various market mechanisms, and to analyze the obtained asset prices, agent-based models can bridge the gap between the micro level of individual investor behavior and the macro level of aggregate market phenomena. It has been recognized, yet not fully explored, that these models could be used as a tool to generate or test various behavioral hypothesis.

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense cat-egorization (prototypical and exemplars-based categorization) with standard monotonic cate-gorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and –in addition– that it may be plausibly applied to different general computational models of cognition. The current version of the system , in fact, extends our previous work, in that Dual-PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation.

This (now somewhat outdated) annotated bibliography brings together qualitative research methodology and cognitive systems theory. This was written for a unique situation. I had to bring these two topic areas together to leverage the considerable expertise of two of my committee members, and learned a great deal in the process. The committee devised questions based on this document and I had to respond to those questions in a 24 hour written exam (not included). This document should be of interest to students seeking methodological tools for studying cognition in real world situations, like music making.

I am currently working on new methodological material. Stay tuned.

Özet: Birden fazla anlama sahip herhangi bir sözcüğün tümce içerisindeki yeri önemli olmaksizin, hangi anlamda olduğu ile ilgili genellikle bir belirsizlik mevcuttur. Kişi, anlam belirsizliği olan bir tümceyi anladiği zaman belirsizliğe neden olan sözcüğün diğer anlamlarini elemiş, sadece bir anlamini göz önüne almiştir. İnsanoğlu anlama işlemini gerçekleştiren bilişsel bir sisteme sahip olduğu için, belirsizlik içeren bir tümcenin anlaşilmasi insan dil

Although the notion of collective intentionality has received considerable attention over the past decade, accounts of collective belief and intention remain individualistic. Most accounts analyze group intentional states in terms of a complex set of individual intentional states and, thus, it is individuals not groups that have intentional states. In this paper, I attempt to undermine one of the motivations for refusing to acknowledge groups as the bearers of mental states. The resistance to collective mental states is motivated by the view that mental states are located in minds and minds are in heads. Since groups do not have heads or brains, they cannot have minds or mental states. There is a significant and important thesis in cognitive science, however, which suggests that the mind is not bounded by skin and bones. If ''the mind ain't in the head'', then this removes a major barrier to the idea of collective minds.

Organizational knowledge is at the center of the debate focused on the nature of knowledge, where the perspective of knowledge as possession opposes the perspective of knowledge as practice. These two views are rooted in the radical versions of realist and constructivist epistemology, respectively, according to which knowledge is an object or a practice. Far from being a Byzantine dispute, the adoption of one or the other has relevant and concrete consequences for the design and management of IS/IT, because as such, the two paradigms result incommensurable in both theoretical and methodological aspects. However, from a moderate and middle-ground version the following fruitful implications would stem: 1) the juxtaposition would dissolve, and a dual nature of knowledge as object and practice would emerge; 2) the epistemology of pragmatism would be able to account for all the concepts and methods employed by the two fronts, thus terminating a sterile “paradigm war”; 3) the theory of autopoiesis would become irrelevant and eventually even misleading; 4) standard scientific methodologies and simulation models would be acknowledged as useful and common tools for progressive confrontations among the supporters of both the paradigms; 5) the development of IS/IT studies and the design of knowledge management systems would substantially benefit.

Working memory (WM) is a cognitive system that strongly relates to a person's ability to reason with novel information and direct attention to goal-relevant information. Due to the central role that WM plays in general cognition, it has become the focus of a rapidly growing training literature that seeks to affect broad cognitive change through prolonged training on WM tasks. Recent work has suggested that the effects of WM training extend to general fluid intelligence, attentional control, and reductions in symptoms of ADHD. We present a theoretically motivated perspective of WM and subsequently review the WM training literature in light of several concerns. These include (a) the tendency for researchers to define change to abilities using single tasks, (b) inconsistent use of valid WM tasks, (c) no-contact control groups, and (d) subjective measurement of change. The literature review highlights several findings that warrant further research but ultimately concludes that there is a need to directly demonstrate that WM capacity increases in response to training. Specifically, we argue that transfer of training to WM must be demonstrated using a wider variety of tasks, thus eliminating the possibility that results can be explained by task specific learning. Additionally, we express concern that many of the most promising results (e.g., increased intelligence) cannot be readily attributed to changes in WM capacity. Thus, a critical goal for future research is to uncover the mechanisms that lead to transfer of training.

This last chapter is intended to clarify some central methodological aspects of morphodynamical abduction as regards dynamical systems and the catastrophe theory. Some problems arise in the classical computational approach to cognition in describing the most interesting abductive issues. A cognitive process (and thus abduction) is described by the manipulation of internal semiotic representations of external world. This view assumes a discrete set of representations fixed in discrete time jumps and, because of its functionalist character, cannot render the embodied dimension of cognition and the issue of anticipation and causation of a new hypothesis adequately. An integration of the traditional computational view with some ideas developed within the so-called dynamical approach and catastrophe theory can lead to important insights. What is the role of abduction in the dynamical system approach?What is the role of the “salient/pregnant” dichotomy with respect to abduction?What is embodied cognition from the point of view of its “physics”?

Embodiment has become the raison d'etre for much of the new 'cognitive robotics'. It fills a gap in the non-interactivist approach of traditional artificial intelligence (AI) in which 'intelligence' is viewed as the manipulation of symbols in a vacuum. However, a foundational question for the new AI is, can embodiment lead to a strong AI, i.e. a robot mind? To address this question, two extreme poles of embodiment are distinguished here, mechanistic and phenomenal. A detailed exploration of each type of embodiment is provided together with an appraisal of whether strong embodiment is possible for robotics, or whether robotics merely provides a tool for scientific exploration and modelling, i.e. weak embodiment? It is argued that strong embodiment, either mechanistic or phenomenal, is not possible for present day robots. However, weak embodiment may provide an enlightened approach to using robots for modelling cognition.

This paper considers the relation between the pragmatic abilities used to interpret communicative behaviour and more general mind-reading abilities used to interpret ordinary actions. According to the classical Fodorian view (Fodor 1983), pragmatics and mind-reading are central cognitive systems which are used to attribute mental states to others on the basis of generalpurpose reasoning abilities. I will outline an alternative, relevance-theoretic account on which mind-reading is a dedicated inferential module, and pragmatics is a sub-module of the mind-reading module, with its own specialpurpose principles and mechanisms.

Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation of models does not depend on whether they target real biological agents or not; instead, the standards of evaluation depend on the use of models rather than on the reality of their targets. I discuss how models are validated depending on their use and argue that all-encompassing benchmarks for models may be well beyond reach.

Concept representation is still an open problem in the field of ontology engineering and, more generally, of knowledge representation. In particular, the issue of representing "non classical" concepts, i.e. concepts that cannot be defined in terms of necessary and sufficient conditions, remains unresolved. In this paper we review empirical evidence from cognitive psychology, according to which concept representation is not a unitary phenomenon. On this basis, we sketch some proposals for concept representation, taking into account suggestions from psychological research. In particular, it seems that human beings employ both prototype-based and exemplar-based representations in order to represent non classical concepts. We suggest that a similar, hybrid prototype-exemplar based approach could also prove useful in the field of knowledge representation technology. Finally, we propose conceptual spaces as a suitable framework for developing some aspects of this proposal.

This chapter builds an account of the cognitive abilities and mechanisms required to produce creative problem-solving and insight. Such mechanisms are identified in an essentialized set of human abilities: making visuospatial inferences, creatively solving problems involving object affordances, using experience with previously solved problems to find solutions for new problems, generating new concepts out of old ones. Each such cognitive ability is selected to suggests a principle necessary for the harder feat of engineering insight. The features such abilities presuppose in a cognitive system are addressed. A core set of mechanisms able to support such features is proposed. A unified system framework in line with cogni-tive research is suggested, in which the knowledge-encoding supports the variety of such processes efficiently.

Why is vocal music the oldest and still the most popular form of music? Very possibly because vocal music involves an intimate combination of speech and music, two of the most specific, high-level skills of human beings. The issue we address is whether people listening to a song treat the linguistic and musical components separately or integrate them within a single percept. Event-related potentials were recorded while musicians listened to excerpts from operas sung a capella. Excerpts were ended by semantically congruous or incongruous words sung either in or out of key. Results clearly demonstrated the independence of lyrics and tunes, so that an additive model of semantic-and harmonic-violations processing predicted the data extremely well. These results are consistent with a modular organization of the human cognitive system and open new perspectives in the search for the similarities and differences between language and music processing.

Embodied cognition is sweeping the planet. On a non-embodied approach, the sensory system informs the cognitive system and the motor system does the cognitive system's bidding. There are causal relations between the systems but the sensory and motor systems are not constitutive of cognition. For embodied views, the relation to the sensori-motor system to cognition is constitutive, not just causal. This paper examines some recent empirical evidence used to support the view that cognition is embodied and raises questions about some of the claims being made by supporters.

In this paper we present some results from an experimental study that we have been conducting into the effects of syntactic attrition on the L1 of Greek and Italian speakers who have achieved near-native proficiency in their L2 (English) but still use their L1 on a regular basis. In particular, we test the hypothesis, developed on the basis of assumptions regarding syntactic modularity, that the changes in L1 syntax will be restricted to the interface with the conceptual / intentional cognitive systems. The area of investigation is the domain of grammatical subjects in Greek and Italian. More specifically, we tested the participants on the production and interpretation of null and overt subjects, and of preverbal and postverbal subjects. We also elicited grammaticality judgments on subject extraction and subject position in various syntactic contexts. In this paper we report on the results of one of the production tasks (of preverbal and postverbal subjects) and two interpretation tasks. Attrition effects are found in the production of preverbal subjects in the Greek group whereas Italian speakers show attrition effects in the interpretation of overt pronominal subjects. We argue that these results are in the right direction, that is, that semantic features are vulnerable in language attrition whereas syntactic options remain intact.

The development of robotic cognition and the advancement of understanding of human cognition form two of the current greatest challenges in robotics and neuroscience, respectively. The RobotCub project aims to develop an embodied robotic child (iCub) with the physical (height 90 cm and mass less than 23 kg) and ultimately cognitive abilities of a 2.5-year-old human child. The iCub will be a freely available open system which can be used by scientists in all cognate disciplines from developmental psychology to epigenetic robotics to enhance understanding of cognitive systems through the study of cognitive development. The iCub will be open both in software, but more importantly in all aspects of the hardware and mechanical design. In this paper the design of the mechanisms and structures forming the basic 'body' of the iCub are described. The papers considers kinematic structures dynamic design criteria, actuator specification and selection, and detailed mechanical and electronic design. The paper concludes with tests of the performance of sample joints, and comparison of these results with the design requirements and simulation projects.

AutoTutor is a computer tutor that simulates the discourse patterns and pedagogical strategies of a typical human tutor. AutoTutor is designed to assist college students in learning the fundamentals of hardware, operating systems, and the Internet in an introductory computer literacy course. Most tutors in school systems are not highly trained in tutoring techniques and have only a modest expertise on the tutoring topic, but they are surprisingly effective in producing learning gains in students. We have dissected the discourse and pedagogical strategies these unskilled tutors exhibit by analyzing approximately 100 hours of naturalistic tutoring sessions. These mechanisms are implemented in AutoTutor. AutoTutor presents questions and problems from a curriculum script, attempts to comprehend learner contributions that are entered by keyboard, formulates dialog moves that are sensitive to the learner's contributions (such as short feedback, pumps, prompts, elaborations, corrections, and hints), and delivers the dialog moves with a talking head. AutoTutor has seven modules: a curriculum script, language extraction, speech act classification, latent semantic analysis, topic selection, dialog move generation, and a talking head. (A.C. Graesser) like AutoTutor, particularly in an academic environ-1389-0417 / 99 / $ -see front matter

Abstract At the most fundamental biological level the brain can be regarded as an organ which functions as a controller of basic homeostatic processes. In terms of its primary structure the brain is grossly composed of three parts: the brain stem, the cerebellum, and the cerebrum. Control is carried out at an innate level by the brain stem, and at a learning based level by the cerebellum and cerebrum. The "hybrid" control facilitated by the interaction of the cerebellum and cerebrum involves communication between the two learning based systems, and this is a particularly important feature in relation to understanding psychological processes. It is proposed that, as a starting point for understanding the function of the brain and its relationship to psychological development and psychological processes, the "core architecture" of the brain can most usefully be described a three tier nested hierarchy of brainstem, cerebellum cerebrum.

The focus of this special issue is on the cognitive load underlying processes of interactive knowledge construction in a wide range of instructional multimedia platforms. Multimedia comprehension involves the parallel processing of auditory–verbal and visual–pictorial channels within working memory. By means of integrating multimodal information, students are able to acquire new knowledge. However, the processes of knowledge construction may be dependent on the load a task imposes on the learner's cognitive system. Such cognitive load is determined by prior knowledge, motivation, and processing strategies on the part of the learner as well as on task demands. Other critical factors that should be explored are goal adoption and perspective taking, effects of interactive animation, environmental support, and possibilities of collaboration.

This survey presents an overview of the autonomous development of mental capabilities in computational agents. It does so based on a characterization of cognitive systems as systems which exhibit adaptive, anticipatory, and purposive goal-directed behavior. We present a broad survey of the various paradigms of cognition, addressing cognitivist (physical symbol systems) approaches, emergent systems approaches, encompassing connectionist, dynamical, and enactive systems, and also efforts to combine the two in hybrid systems. We then review several cognitive architectures drawn from these paradigms. In each of these areas, we highlight the implications and attendant problems of adopting a developmental approach, both from phylogenetic and ontogenetic points of view. We conclude with a summary of the key architectural features that systems capable of autonomous development of mental capabilities should exhibit

""As map-based visualizations of documents become more ubiquitous, there is a greater need for them to support intellectual and creative high-level cognitive activities with collections of non-cartographic materials — documents. This dissertation concerns the conceptualization of map-based visualizations as tools for sensemaking and collection understanding. As such, map-based visualizations would help people use georeferenced documents to develop understanding, gain insight, discover knowledge, and construct meaning.

This dissertation explores the role of graphical representations (such as maps, Kohonen maps, pie charts, and other) and interactions with them for developing map-based visualizations capable of facilitating sensemaking activities such as collection understanding. While graphical representations make document collections more perceptually and cognitively accessible, interactions allow users to adapt representations to users’ contextual needs. By interacting with representations of documents or collections and being able to construct representations of their own, people are better able to make sense of information, comprehend complex structures, and integrate new information into their existing mental models. In sum, representations and interactions may reduce cognitive load and consequently expedite the overall time necessary for completion of sensemaking activities, which typically take much time to accomplish.

The dissertation proceeds in three phases. The first phase develops a conceptual framework for translating ontological properties of collections to representations and for supporting visual tasks by means of graphical representations. The second phase concerns the cognitive benefits of interaction. It conceptualizes how interactions can help people during complex sensemaking activities. Although the interactions are explained on the example of a prototype built with Google Maps, they are independent of Google Maps and can be applicable to various other technologies. The third phase evaluates the utility, analytical capabilities and usability of the additional representations when users interact with a visualization prototype – VIsual COLlection EXplorer. The findings suggest that additional representations can enhance understanding of map-based visualizations of library collections: specifically, they can allow users to see trends, gaps, and patterns in ontological properties of collections.""

The newer version of VICOLEX is available at: http://abuchel.physics.uwo.ca/~obuchel/VICOLEX/map4.php

So far, meaning constitution and processing in artificial information systems has been supported either by merely rule-based local and distributed algorithmic processes, or by purely dynamic processes of self-organization. These approaches differ due the fact that the former accepts the need of representations which are viewed as sequences of symbols being manipulated by externally given apriori rules, while the latter tries to understand natural cognitive systems from the perspective of dynamics, and keep at the same time, a non-computational and non-representational stance. Both these cases are characterized by the inadequacy to handle the emergent phenomena that characterize complex information systems, since they either process information based on static meaning structures, or their internal variety and discrimination ability cannot exhibit open-ended evolution. On the other hand, meaning structures may emerge in a communicative/cognitive framework that supports interaction. In this paper, an inclusive systems theoretic framework which supports the emergence of meaning structures from the semiotic interaction of selforganized cognitive systems is investigated, in terms of its main components and their relations. It is argued that representations are a necessary element in meaning-based interaction, but they should be defined with respect to, and in the context of, the semiotic behaviour of a system within an environment. It is believed that the richness of the discussed framework can offer fresh impetus to the design and implementation of meaning-based evolving information systems.

In a dynamic world, mechanisms allowing prediction of future situations can provide a selective advantage. We suggest that memory systems differ in the degree of flexibility they offer for anticipatory behavior and put forward a corresponding taxonomy of prospection. The adaptive advantage of any memory system can only lie in what it contributes for future survival. The most flexible is episodic memory, which we suggest is part of a more general faculty of mental time travel that allows us not only to go back in time, but also to foresee, plan, and shape virtually any specific future event. We review comparative studies and find that, in spite of increased research in the area, there is as yet no convincing evidence for mental time travel in nonhuman animals. We submit that mental time travel is not an encapsulated cognitive system, but instead comprises several subsidiary mechanisms. A theater metaphor serves as an analogy for the kind of mechanisms required for effective mental time travel. We propose that future research should consider these mechanisms in addition to direct evidence of future-directed action. We maintain that the emergence of mental time travel in evolution was a crucial step towards our current success.

This paper reports a series of experiments that were carried out in order to study the attentional system. Three networks make up this system, and each of them specializes in particular processes. The executive control network specializes in control processes, such as conflict resolution or detection of errors; the orienting network directs the processing system to the source of input and enhances its processing; the alerting network prepares the system for a fast response by maintaining an adequate level of activation in the cognitive system. Recently, Fan and collaborators [J Cogn Neurosci 14(3):340-347, 2002] designed a task to measure the efficiency of each network. We modified Fan's task to test the influences among the networks. We found that the executive control network is inhibited by the alerting network, whereas the orienting network raises the efficiency of the executive control network (Experiment 1). We also found that the alerting network influences the orienting network by speeding up its time course function (Experiment 2). Results were replicated in a third experiment, proving the effects to be stable over time, participants and experimental context, and to be potentially important as a tool for neuropsychological assessment.

The mother tongue of the absolute majority of native Arabic speakers is Spoken Arabic (SA), which is a local dialect that does not have a written form. For reading and writing, as well as for formal communication Literary Arabic (LA) is used. For the literate Arabs, these two languages are extensively inter-twined in every day life. Consequently, it is possible that, despite the difference between them, LA is not processed like a regular second language by the cognitive system of the native Arabic speakers but rather as an enhancement of the spoken lexicon. In the present study we examined this possibility comparing semantic priming effects in auditory lexical decision within SA (L1), with the effects found across languages with LA or in Hebrew (L2). Hebrew is doubtlessly a second language for native Arabic speakers. In this study we have manipulated semantic priming. In Experiment 1 the targets were in Spoken Arabic and the primes in any of the three languages. The semantic priming effect was twice as large within L1 as between languages and there was no difference between Hebrew and LA. In Experiment 2, all primes were in SA whereas the targets were in any of the three languages. The priming effects in that experiment were doubled relative to the previous experiment, but the inter-language relationships were the same. For both language pairings, the semantic priming was larger when the primes were presented in SA (and the targets in either Hebrew or LA) than when the primes were presented in one of the second languages and the targets in SA. The conclusion is that, despite the intensive daily use adult native Arabic speakers make of SA and LA, and despite their shared origin, the two languages retain their status as first and second languages in the cognitive system.

Through the preferential pairing of response positions to pitch, here we show that the internal representation of pitch height is spatial in nature and affects performance, especially in musically trained participants, when response alternatives are either vertically or horizontally aligned. The finding that our cognitive system maps pitch height onto an internal representation of space, which in turn affects motor

In computational cognitive science, many cognitive processes seem to be successfully modeled as Bayesian computations. Yet, many such Bayesian computations have been proven to be computationally intractable (NP-hard) for unconstrained input domains, even if only an approximate solution is sought. This computational complexity result seems to be in strong contrast with the ease and speed with which humans can typically make the inferences that are modeled by Bayesian models. This contrast-between theory and practice-poses a considerable theoretical challenge for computational cognitive modelers: How can intractable Bayesian computations be transformed into computationally plausible 'approximate' models of human cognition? In this paper, three candidate notions of 'approximation' are discussed, each of which has been suggested in the cognitive science literature. We will sketch how (parameterized) computational complexity analyses can yield model variants that are tractable and which can serve as the basis of computationally plausible models of cognition.

The development of robotic cognition and the advancement of understanding of human cognition form two of the current greatest challenges in robotics and neuroscience, respectively. The RobotCub project aims to develop an embodied robotic child (iCub) with the physical (height 90 cm and mass less than 23 kg) and ultimately cognitive abilities of a 2.5-year-old human child. The iCub will be a freely available open system which can be used by scientists in all cognate disciplines from developmental psychology to epigenetic robotics to enhance understanding of cognitive systems through the study of cognitive development. The iCub will be open both in software, but more importantly in all aspects of the hardware and mechanical design. In this paper the design of the mechanisms and structures forming the basic 'body' of the iCub are described. The papers considers kinematic structures dynamic design criteria, actuator specification and selection, and detailed mechanical and electronic design. The paper concludes with tests of the performance of sample joints, and comparison of these results with the design requirements and simulation projects.

The question is not whether intelligent machines can have any emotions, but whether machines can be intelligent without any emotions. -Marvin Minsky, (Minsky, 1986) p. 163 In every art form it is the emotional content that makes the difference between mere technical skill and true art. -The Illusion of Life: Disney Animation (Thomas & Johnston, 1995) p. 473 You don't get emotions by manipulating 0s and 1s.

The creative problem-solving performed by natural cognitive systems includes a wide variety of tasks of different degrees of difficulty. A classification of creative problems in two broad categories is proposed, based on problem structuredness and the cognitive processes used in regulating the problem structure-representation structure relationship in creative problem-solving. A cognitive theoretical framework is used to exemplify the difference in cognitive processes participation in these two classes of creative problem solving.

Synthesizing existing work from diverse disciplines, this paper introduces a culture-gene coevolutionary approach to human behavior and psychology, and applies it to the evolution of cooperation. After a general discussion of cooperation in humans, this paper summarizes Dual Inheritance Theory and shows how cultural transmission can be brought under the Darwinian umbrella in order to analyze how culture and genes coevolve and jointly influence human behavior and psychology. We then present a generally applicable mathematical characterization of the problem of cooperation. From a Dual Inheritance perspective, we review and discuss work on kinship, reciprocity, reputation, social norms, and ethnicity, and their application to solving the problem of cooperation.

Analogical reasoning is a highly sophisticated cognitive process and it could be the missing link for the understanding of cognitive abilities in natural complex systems. In many current approaches for modeling analogies and analogical reasoning, cognitive abilities are examined in isolation from related issues in order to control the environment and the underlying context. Although these research endeavors are successful in various aspects and applications, it seems as if each result of modeling a particular ability minimizes the chances to reach overall goals like modeling human-level intelligence. With this workshop we aim to bring together researchers who are working in the field of analogical reasoning and are relating their models to other cognitive abilities. This workshop focuses on analogy as an integrating basis for human cognition.

Current understanding of sources of fatigue and of how fatigue affects performance in prolonged cognitive tasks is limited. We have observed that participants improve in response time but decrease in accuracy after extended repetitive work in a data entry task. We attributed the increase in errors to accumulating fatigue and the reduction in response time to learning. The concurrent effects of fatigue and learning seem intuitively reasonable but have not been explained computationally. This paper presents a cognitive computational model of these effects. The model, developed using the ACT-R cognitive architecture (1 and 3), accounts for learning and fatigue effects through a time-dependent modification of architectural parameters. The model is tested against human data from two independent experiments. Best fit to human accuracy and total response time was found from a modulation of both cognitive and arousal processes. Implications for training and skill acquisition research are discussed.

The paper proposes a novel cognitive architecture (CA) for computational creativity based on the Psi model and on the mechanisms inspired by dual process theories of reasoning and rationality. In recent years, many cognitive models have focused on dual process theories to better describe and imple- ment complex cognitive skills in artificial agents, but creativity has been approached only at a descriptive level. In previous works we have described various modules of the cognitive architecture that allows a robot to execute creative paintings. By means of dual process theories we refine some relevant mechanisms to obtain artworks, and in particular we explain details about the resolution level of the CA dealing with different strategies of access to the Long Term Memory (LTM) and managing the interaction between S1 and S2 processes of the dual process theory. The creative process involves both divergent and convergent processes in either implicit or explicit manner. This leads to four activities (exploratory, reflective, tacit, and analytic) that, triggered by urges and motivations, generate creative acts. These creative acts exploit both the LTM and the WM in order to make novel substitutions to a perceived image by properly mixing parts of pictures coming from differ- ent domains. The paper highlights the role of the interaction between S1 and S2 processes, modulated by the resolution level, which focuses the attention of the creative agent by broadening or narrowing the exploration of novel solutions, or even drawing the solution from a set of already made associations. An example of artificial painter is described in some experimentations by using a robotic platform.

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 onedimensional 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.

This article presents a theoretical discussion of the relationship between language and communication. I discuss Chomsky's position on this topic. Chomsky claims that if it is possible to construct a scientific theory of the language faculty, there is no possibility to construct a scientific theory of communication because in communication human intentionality is involved. This position is contrasted by philosophers of language considering that communication is to be studied as a form of rational action. I maintain that both these positions are not supported by the evidence coming from developmental research. Taking a cognitive point of view I contend that a communicative faculty can be defined that develops since infancy to adulthood, which has features independent of language and action. Different steps in the development of the communicative ability are linked to a parallel development of the theory of mind. I then argue in favor of a distinction between collective action and communication considering that while collective action is common to human and nonhuman primates, communication is typically human.

The aim of this paper is to develop a theoretical model and a set of terms for understanding and discussing how we recognize familiar faces, and the relationship between recognition and other aspects of face processing. It is suggested that there are seven distinct types of information that we derive from seen faces; these are labelled pictorial, structural, visually derived semantic, identity-specific semantic, name, expression and facial speech codes. A functional model is proposed in which structural encoding processes provide descriptions suitable for the analysis of facial speech, for analysis of expression and for face recognition units. Recognition of familiar faces involves a match between the products of structural encoding and previously stored structural codes describing the appearance of familiar faces, held in face recognition units. Identity-specific semantic codes are then accessed from person identity nodes, and subsequently name codes are retrieved. It is also proposed that the cognitive system plays an active role in deciding whether or not the initial match is sufficiently close to indicate true recognition or merely a 'resemblance'; several factors are seen as influencing such decisions.

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.

First, this article proposes a minimal definition of embodiment that can be applied across animals and artefacts. We discuss the potential contributions of this operational definition with respect to assessing and measuring the degree of embodiment in different biological and artificial systems. Second, we outline how this definition can be extended to lead to the particular notion of social embeddedness. Socially embedded agents are structurally coupled with their social environment, in that their sensorimotor activity is grounded in the social environment that the agent is surrounded by. Lastly, based on research in the social sciences on human-human interaction, we discuss perceptual requirements for interaction-aware robotic agentsagents whose identification and interpretation of the (social) environment is facilitated by awareness of the structure of agent-agent interactions (including humans 'in the loop'). We suggest relevant concepts and heuristics that can contribute to studies of degrees of embodiment of robots that interact with social environments. Manipulating and systematically investigating these heuristics permits variation of the degree of embodiment of such interaction-aware robots. 

The move toward a dynamical and embodied understanding of cognitive processes initiated a debate about the usefulness of the notion of representation for cognitive science. The debate started when some proponents of a dynamical and embodied approach argued that the use of representations could be discarded in many circumstances. This remained a minority view, however, and there is now a tendency to shove this critique of the usefulness of representations aside as a non-issue for a dynamical and situated approach to cognition. In opposition, I will argue that the representation issue is far from settled, and instead forms the kernel of an important conceptual shift between traditional cognitive science and a dynamical and embodied approach. This will be done by making explicit the key features of representation in traditional cognitive science and by arguing that the representation-like entities that come to the fore in a dynamical and embodied approach are significantly different from the traditional notion of representation. This difference warrants a change of terminology to signal an important change in meaning. 

We present the input to the discussion about the computational framework known as Common Model of Cognition (CMC) from the working group dealing with the knowledge/rational/social levels. In particular, we present a list of the higher level constraints that should be addressed within such a general framework.

The paper introduces an extension of the proposal according to which conceptual representations in cognitive agents should be intended as heterogeneous proxytypes. The main contribution of this paper is in that it details how to reconcile, under a heterogeneous representational perspective, different theories of typicality about conceptual representation and reasoning. In particular, it provides a novel theoretical hypothesis-as well as a novel categorization algorithm called DELTA-showing how to integrate the representational and reasoning assumptions of the theory-theory of concepts with the those ascribed to the prototype and exemplars-based theories.

Un des objectifs de cette étude était de préciser l'impact du vieillissement sur l'apprentissage d'un labyrinthe. Il a aussi été question de préciser l'implication relative des divers systèmes qui semblent impliqués dans l'apprentissage d'un labyrinthe, soit les fonctions exécutives, l'apprentissage procédural et la mémoire de travail. Pour ce faire, une tâche informatisée de labyrinthe utilisant un écran tactile a été développée. Les participants ont été aussi soumis à une batterie de tests neuropsychologiques qui mesurent séparément divers aspects de la mémoire, la mémoire de travail, ainsi que l'apprentissage procédural. Deux échantillons de sujets ont participé à cette étude : 20 jeunes adultes âgés entre 20 et 30 ans, 19 personnes âgées entre 58 et 72 ans. Les résultats obtenus montrent que le vieillissement affecte ce type d'apprentissage d'un labyrinthe. Le déclin dans la performance des personnes âgées est caractérisé par un plus grand nombre de déplacements, par un parcours plus lent et par un plus grand nombre d'erreurs persévératives à la tâche du labyrinthe. De plus, la faible performance des personnes âgées à la tâche procédurale et le grand nombre d'erreurs de persévération sont les composantes principalement impliquées dans le ralentissement cognitif des participants à la tâche informatisée de labyrinthe, confirmant ainsi le rôle des fonctions exécutives et de l'apprentissage procédural dans ce type de tâche. © 2005 Elsevier SAS. Tous droits réservés.

This book contains the accepted papers at ProSocrates'17 Symposium: Problem-solving, Creativity and Spatial Reasoning in Cognitive Systems 1 . ProSocrates'17 symposium was held at the Hansewissenschaftkolleg (HWK) of Advanced Studies in Delmenhorst, 20-21 July 2017. This was the second edition of this symposium which tries to bring together researchers interested in spatial reasoning, problem solving and creativity.

The recency effect in free recall features prominently in 1960s' theorizing about short-term memory, but has since been largely ignored. We argue that this stems from a preoccupation with the role of recency in the concept of primary memory and the neglect of its role in a broader working-memory framework. It is suggested that the recency effect reflects the application of an explicit retrieval strategy to the residue of implicit learning within a range of cognitive systems. When retrieved implicitly, the same residue is assumed to form the basis of priming effects. The various criteria for implicit learning described by are successfully applied to the recency effect, and a retrieval process is outlined that can account for both longand short-term recency effects. It is suggested that a framework combining recency, priming, and implicit learning provides a basis for understanding one of the most important features of cognition and memory, namely, that of maintaining orientation in time and place.