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  1.  76
    The Interaction of the Explicit and the Implicit in Skill Learning: A Dual-Process Approach.Ron Sun - 2005 - Psychological Review 112 (1):159-192.
    This article explicates the interaction between implicit and explicit processes in skill learning, in contrast to the tendency of researchers to study each type in isolation. It highlights various effects of the interaction on learning (including synergy effects). The authors argue for an integrated model of skill learning that takes into account both implicit and explicit processes. Moreover, they argue for a bottom-up approach (first learning implicit knowledge and then explicit knowledge) in the integrated model. A variety of qualitative data (...)
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  2.  34
    Duality of the Mind.Ron Sun - manuscript
    Synthesizing situated cognition, reinforcement learning, and hybrid connectionist modeling, a generic cognitive architecture focused on situated involvement and interaction with the world is developed in this book. The architecture notably incorporates the distinction of implicit and explicit processes.
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  3.  10
    Incubation, Insight, and Creative Problem Solving: A Unified Theory and a Connectionist Model.Sébastien Hélie & Ron Sun - 2010 - Psychological Review 117 (3):994-1024.
  4.  82
    Incubation, Insight, and Creative Problem Solving: A Unified Theory and a Connectionist Model.Ron Sun - 2010 - Psychological Review 117 (3):994-1024.
    This article proposes a unified framework for understanding creative problem solving, namely, the explicit–implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of incubation and insight). The explicit–implicit interaction theory relies mainly on 5 basic principles, namely, (a) the coexistence of and the difference between explicit and implicit knowledge, (b) the simultaneous involvement of implicit and explicit processes in most (...)
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  5.  52
    The Cambridge Handbook of Computational Psychology.Ron Sun (ed.) - 2008 - Cambridge University Press.
    This book is a definitive reference source for the growing, increasingly more important, and interdisciplinary field of computational cognitive modeling, that is, computational psychology. It combines breadth of coverage with definitive statements by leading scientists in this field. Research in computational cognitive modeling explores the essence of cognition through developing detailed, process-based understanding by specifying computational mechanisms, structures, and processes. Computational models provide both conceptual clarity and precision at the same time. This book substantiates this approach through overviews and many (...)
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  6.  52
    On Levels of Cognitive Modeling.Ron Sun, L. Andrew Coward & Michael J. Zenzen - 2005 - Philosophical Psychology 18 (5):613-637.
  7.  58
    Motivational Representations Within a Computational Cognitive Architecture.Ron Sun - unknown
    This paper discusses essential motivational representations necessary for a comprehensive computational cognitive architecture. It hypothesizes the need for implicit drive representations, as well as explicit goal representations. Drive representations consist of primary drives — both low-level primary drives (concerned mostly with basic physiological needs) and high-level primary drives (concerned more with social needs), as well as derived (secondary) drives. On the basis of drives, explicit goals may be generated on the fly during an agent’s interaction with various situations. These motivational (...)
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  8. Theoretical Status of Computational Cognitive Modeling.Ron Sun - unknown
    This article explores the view that computational models of cognition may constitute valid theories of cognition, often in the full sense of the term ‘‘theory”. In this discussion, this article examines various (existent or possible) positions on this issue and argues in favor of the view above. It also connects this issue with a number of other relevant issues, such as the general relationship between theory and data, the validation of models, and the practical benefits of computational modeling. All the (...)
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  9. Top-Down Versus Bottom-Up Learning in Cognitive Skill Acquisition.Ron Sun - unknown
    This paper explores the interaction between implicit and explicit processes during skill learning, in terms of top-down learning (that is, learning that goes from explicit to implicit knowledge) versus bottom-up learning (that is, learning that goes from implicit to explicit knowledge). Instead of studying each type of knowledge (implicit or explicit) in isolation, we stress the interaction between the two types, especially in terms of one type giving rise to the other, and its effects on learning. The work presents an (...)
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  10.  65
    Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model.Ron Sun - manuscript
    Most of the work in agent-based social simulation has assumed highly simplified agent models, with little attention being paid to the details of individual cognition. Here, in an effort to counteract that trend, we substitute a realistic cognitive agent model (CLARION) for the simpler models previously used in an organizational design task. On that basis, an exploration is made of the interaction between the cognitive parameters that govern individual agents, the placement of agents in different organizational structures, and the performance (...)
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  11. On Levels of Cognitive Modeling.Ron Sun, Andrew Coward & Michael J. Zenzen - 2005 - Philosophical Psychology 18 (5):613-637.
    The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical sciences, a rigorous set of theories is a hierarchy of descriptions/explanations, in which causal relationships among entities at a high (...)
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  12.  66
    Accounting for the Computational Basis of Consciousness: A Connectionist Approach.Ron Sun - 1999 - Consciousness and Cognition 8 (4):529-565.
    This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the (...)
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  13.  98
    Desiderata for Cognitive Architectures.Ron Sun - 2004 - Philosophical Psychology 17 (3):341-373.
    This article addresses issues in developing cognitive architectures--generic computational models of cognition. Cognitive architectures are believed to be essential in advancing understanding of the mind, and therefore, developing cognitive architectures is an extremely important enterprise in cognitive science. The article proposes a set of essential desiderata for developing cognitive architectures. It then moves on to discuss in detail some of these desiderata and their associated concepts and ideas relevant to developing better cognitive architectures. It argues for the importance of taking (...)
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  14.  38
    Cognitive Science Meets Multi-Agent Systems: A Prolegomenon.Ron Sun - 2001 - Philosophical Psychology 14 (1):5 – 28.
    In the current research on multi-agent systems (MAS), many theoretical issues related to sociocultural processes have been touched upon. These issues are in fact intellectually profound and should prove to be significant for MAS. Moreover, these issues should have equally significant impact on cognitive science, if we ever try to understand cognition in the broad context of sociocultural environments in which cognitive agents exist. Furthermore, cognitive models as studied in cognitive science can help us in a substantial way to better (...)
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  15.  55
    Multi-Agent Reinforcement Learning: Weighting and Partitioning.Ron Sun & Todd Peterson - unknown
    This paper addresses weighting and partitioning in complex reinforcement learning tasks, with the aim of facilitating learning. The paper presents some ideas regarding weighting of multiple agents and extends them into partitioning an input/state space into multiple regions with di erential weighting in these regions, to exploit di erential characteristics of regions and di erential characteristics of agents to reduce the learning complexity of agents (and their function approximators) and thus to facilitate the learning overall. It analyzes, in reinforcement learning (...)
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  16.  85
    Learning, Action, and Consciousness: A Hybrid Approach Toward Modeling Consciousness.Ron Sun - 1997 - Neural Networks 10:1317-33.
    _role, especially in learning, and through devising hybrid neural network models that (in a qualitative manner) approxi-_ _mate characteristics of human consciousness. In doing so, the paper examines explicit and implicit learning in a variety_ _of psychological experiments and delineates the conscious/unconscious distinction in terms of the two types of learning_ _and their respective products. The distinctions are captured in a two-level action-based model C_larion_. Some funda-_ _mental theoretical issues are also clari?ed with the help of the model. Comparisons with (...)
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  17.  82
    The Importance of Cognitive Architectures: An Analysis Based on CLARION.Ron Sun - unknown
    Research in computational cognitive modeling investigates the nature of cognition through developing process-based understanding by specifying computational models of mechanisms (including representations) and processes. In this enterprise, a cognitive architecture is a domaingeneric computational cognitive model that may be used for a broad, multiple-level, multipledomain analysis of behavior. It embodies generic descriptions of cognition in computer algorithms and programs. Developing cognitive architectures is a difficult but important task. In this article, discussions of issues and challenges in developing cognitive architectures will (...)
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  18.  31
    Bottom-Up Skill Learning in Reactive Sequential Decision Tasks.Ron Sun, Todd Peterson & Edward Merrill - unknown
    This paper introduces a hybrid model that unifies connectionist, symbolic, and reinforcement learning into an integrated architecture for bottom-up skill learning in reactive sequential decision tasks. The model is designed for an agent to learn continuously from on-going experience in the world, without the use of preconceived concepts and knowledge. Both procedural skills and high-level knowledge are acquired through an agent’s experience interacting with the world. Computational experiments with the model in two domains are reported.
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  19. Symbol Grounding: A New Look at an Old Idea.Ron Sun - 2000 - Philosophical Psychology 13 (2):149-172.
    Symbols should be grounded, as has been argued before. But we insist that they should be grounded not only in subsymbolic activities, but also in the interaction between the agent and the world. The point is that concepts are not formed in isolation (from the world), in abstraction, or "objectively." They are formed in relation to the experience of agents, through their perceptual/motor apparatuses, in their world and linked to their goals and actions. This paper takes a detailed look at (...)
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  20.  95
    Introduction to Computational Cognitive Modeling.Ron Sun - 2008 - In The Cambridge Handbook of Computational Psychology. Cambridge University Press. pp. 3--19.
  21.  40
    Two Models of Moral Judgment.Shane Bretz & Ron Sun - 2018 - Cognitive Science 42 (S1):4-37.
    This paper compares two theories and their two corresponding computational models of human moral judgment. In order to better address psychological realism and generality of theories of moral judgment, more detailed and more psychologically nuanced models are needed. In particular, a motivationally based theory of moral judgment is developed in this paper that provides a more accurate account of human moral judgment than an existing emotion-reason conflict theory. Simulations based on the theory capture and explain a range of relevant human (...)
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  22.  23
    Potential of full human–machine symbiosis through truly intelligent cognitive systems.Ron Sun - 2020 - AI and Society 35 (1):17-28.
    It is highly likely that, to achieve full human–machine symbiosis, truly intelligent cognitive systems—human-like —may have to be developed first. Such systems should not only be capable of performing human-like thinking, reasoning, and problem solving, but also be capable of displaying human-like motivation, emotion, and personality. In this opinion article, I will argue that such systems are indeed possible and needed to achieve true and full symbiosis with humans. A computational cognitive architecture is used in this article to illustrate, in (...)
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  23.  22
    Effects of Model-Based and Memory-Based Processing on Speed and Accuracy of Grammar String Generation.Robert C. Mathews & Ron Sun - unknown
    Learners are able to use 2 different types of knowledge to perform a skill. One type is a conscious mental model, and the other is based on memories of instances. The authors conducted 3 experiments that manipulated training conditions designed to affect the availability of 1 or both types of knowledge about an artificial grammar. Participants were tested for both speed and accuracy of their ability to generate letter sequences. Results indicate that model-based training leads to slow accurate responding. Memorybased (...)
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  24.  58
    Modeling Meta-Cognition in a Cognitive Architecture.Ron Sun, Xi Zhang & Robert Mathews - unknown
    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 (...)
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  25. Anatomy of Mind: Exploring Psychological Mechanisms & Processes, Clarion Cognitive Architecture.Ron Sun - 2016 - Oxford University Press USA.
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  26. Anatomy of the Mind: Exploring Psychological Mechanisms and Processes with the Clarion Cognitive Architecture.Ron Sun - 2016 - Oup Usa.
    This book aims to understand human cognition and psychology through a comprehensive computational theory of the mind, namely, a "cognitive architecture.".
     
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  27.  33
    A Bottom-Up Model of Skill Learning.Ron Sun, Todd Peterson & Edward Merrill - unknown
    We present a skill learning model CLARION. Different from existing models of high-level skill learning that use a topdown approach (that is, turning declarative knowledge into procedural knowledge), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. CLAR- ION is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line learning. We compare the model with human data in a minefield navigation task. A match between the model and (...)
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  28.  35
    Autonomous Generation of Symbolic Representations Through Subsymbolic Activities.Ron Sun - 2013 - Philosophical Psychology 26 (6):888 - 912.
    This paper explores an approach for autonomous generation of symbolic representations from an agent's subsymbolic activities within the agent-environment interaction. The paper describes a psychologically plausible general framework and its various methods for autonomously creating symbolic representations. The symbol generation is accomplished within, and is intrinsic to, a generic and comprehensive cognitive architecture for capturing a wide variety of psychological processes (namely, CLARION). This work points to ways of obtaining more psychologically/cognitively realistic symbolic and subsymbolic representations within the framework of (...)
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  29. Computational Models of Consciousness: A Taxonomy and Some Examples.Ron Sun & Stan Franklin - 2007 - In Philip David Zelazo, Morris Moscovitch & Evan Thompson (eds.), Cambridge Handbook of Consciousness. Cambridge: Cambridge University Press. pp. 151--174.
  30.  11
    Computational Cognitive Modeling the Source of Power and Other Related Issues.Ron Sun - unknown
    Computational cognitive models hypothesize internal mental processes of human cognitive activities and express such activities by computer programs Such computational models often consist of many components and aspects Claims are often made that certain aspects of the models play a key role in modeling but such claims are sometimes not well justi ed or explored In this paper we rst review some fundamental distinctions and issues in computational modeling We then discuss in principle systematic ways of identifying the source of (...)
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  31.  74
    Computation, Reduction, and Teleology of Consciousness.Ron Sun - 2001 - Cognitive Systems Research 1 (1):241-249.
    This paper aims to explore mechanistic and teleological explanations of consciousness. In terms of mechanistic explanations, it critiques various existing views, especially those embodied by existing computational cognitive models. In this regard, the paper argues in favor of the explanation based on the distinction between localist (symbolic) representation and distributed representation (as formulated in the connectionist literature), which reduces the phenomenological difference to a mechanistic difference. Furthermore, to establish a teleological explanation of consciousness, the paper discusses the issue of the (...)
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  32.  9
    A Response to Núñez Et Al.'S “What Happened to Cognitive Science?”.Marjorie McShane, Selmer Bringsjord, James Hendler, Sergei Nirenburg & Ron Sun - 2019 - Topics in Cognitive Science 11 (4):914-917.
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  33.  12
    Some Experiments with a Hybrid Model for Learning Sequential Decision Making.Ron Sun & Todd Peterson - unknown
    To deal with reactive sequential decision tasks we present a learning model which is a hybrid connectionist model consisting of both localist and distributed representations based on the two level approach proposed in..
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  34. Criteria for an Effective Theory of Consciousness and Some Preliminary Attempts.Ron Sun - 2004 - Consciousness and Cognition 13 (2):268-301.
    In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...)
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  35.  41
    Individual Action and Collective Function: From Sociology to Multi-Agent Learning.Ron Sun - manuscript
    Co-learning of multiple agents has been studied in co-learning settings, and how do they help, or many different disciplines under various guises. For hamper, learning and cooperation? example, the issue has been tackled by distributed • How do we characterize the process and the artificial intelligence, parallel and distributed com- dynamics of co-learning, conceptually, mathe- puting, cognitive psychology, social psychology, matically, or computationally? game theory (and other areas of mathematical econ- • how do social structures and relations interact omics), sociology, (...)
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  36.  11
    A Cognitive Social Simulation of Tribal Survival Strategies: The Importance of Cognitive and Motivational Factors.Ron Sun & Pierson Fleischer - 2012 - Journal of Cognition and Culture 12 (3-4):287-321.
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  37.  50
    Implicit Cognition, Emotion, and Meta-Cognitive Control.Ron Sun & Robert C. Mathews - 2012 - Mind and Society 11 (1):107-119.
    The goal of this research is to understand the interaction of implicit and explicit psychological processes in dealing with emotional distractions and meta-cognitive control of such distractions. The questions are how emotional and meta-cognitive processes can be separated into implicit and explicit components, and how such a separation can be utilized to improve self-regulation of emotion, which can have significant theoretical and practical implications.
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  38.  8
    Self Segmentation of Sequences.Ron Sun - unknown
    chical reinforcement learning that does not rely on a pri ori hierarchical structures Thus the approach deals with a more di cult problem compared with existing work It in volves learning to segment sequences to create hierarchical structures based on reinforcement received during task ex ecution with di erent levels of control communicating with each other through sharing reinforcement estimates obtained by each others The algorithm segments sequences to re duce non Markovian temporal dependencies to facilitate the learning of the (...)
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  39.  69
    The Interaction of Explicit and Implicit Learning: An Integrated Model.Ron Sun - unknown
    This paper explicates the interaction between the implicit and explicit learning processes in skill acquisition, contrary to the common tendency in the literature of studying each type of learning in isolation. It highlights the interaction between the two types of processes and its various effects on learning, including the synergy effect. This work advocates an integrated model of skill learning that takes into account both implicit and explicit processes; moreover, it embodies a bottom-up approach (first learning implicit knowledge and then (...)
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  40.  39
    Mixed Effects of Distractor Tasks on Incubation.Ron Sun - unknown
    suggests that incubation is a diverse phenomenon, involving diverse cognitive processes. Hence, distracting activities can..
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  41.  2
    Exploring Culture From the Standpoint of a Cognitive Architecture.Ron Sun - 2020 - Philosophical Psychology 33 (2):155-180.
    ABSTRACTThis article focuses on the relationship between cultural and cognitive-psychological processes, and discusses the potential impact of the cognitive sciences on understand...
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  42. A Cognitively Based Simulation of Academic Science.Ron Sun - unknown
    The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous (...)
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  43.  37
    Connectionist Inference Models.Ron Sun - manuscript
    The performance of symbolic inference tasks has long been a challenge to connectionists. In this paper, we present an extended survey of this area. Existing connectionist inference systems are reviewed, with particular reference to how they perform variable binding and rule- based reasoning and whether they involve distributed or localist representations. The bene®ts and disadvantages of different representations and systems are outlined, and conclusions drawn regarding the capabilities of connectionist inference systems when compared with symbolic inference systems or when used (...)
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  44.  33
    Integration of Cognitive Systems Across Disciplinary Boundaries.Ron Sun & Gregg C. Oden - unknown
    The present issue is the beginning of a new journal from various sub-disciplines and paradigms in order – Cognitive Systems Research – which we have to construct a coherent picture of how the various developed in response to what we perceive to be an pieces fit together overall. Such a synthesis is unfilled niche in the current literature in the areas of essential to the discovery of designs for general Cognitive Science and Artificial Intelligence.
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  45. A Cognitively Based Simulation of Academic Science.Isaac Naveh & Ron Sun - unknown
    The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous (...)
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  46. Proceedings of the 28th Annual Conference of the Cognitive Science Society.Ron Sun (ed.) - 2006
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  47.  92
    Social Institution, Cognition, and Survival: A Cognitive–Social Simulation.Ron Sun & Isaac Naveh - 2007 - Mind and Society 6 (2):115-142.
    Although computational models of cognitive agents that incorporate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is explored, through simulating survival strategies of tribal societies. The results of the simulation demonstrate interactions between cognitive and social factors. For example, we show that cognitive capabilities and tendencies may be (...)
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  48.  72
    Cognitive Architectures and Multi-Agent Social Simulation.Ron Sun - unknown
    As we know, a cognitive architecture is a domain-generic computational cognitive model that may be used for a broad analysis of cognition and behavior. Cognitive architectures embody theories of cognition in computer algorithms and programs. Social simulation with multi-agent systems can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents (as argued in Sun 2001). In this survey, an example cognitive architecture will be given, and its application to social simulation will be sketched.
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  49.  56
    The Symposium on the Synergy Between Implicit and Explicit Learning Processes.Robert Mathews & Ron Sun - unknown
    Implicit processes are thought to be relatively fast, inaccessible, holistic, and imprecise, while explicit processes are slow, accessible and precise (e.g., Reber, 1989, Sun 2002). This dichotomy is closely related to some other well-known dichotomies including symbolic versus subsymbolic processing (Rumelhart et al., 1986), conceptual versus subconceptual processing (Smolensky, 1988), and conscious versus unconscious processing (Jacoby et al., 1994). This dichotomy has been justified by extensive studies of implicit and explicit learning, implicit and explicit memory, and implicit versus explicit metacognition (...)
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  50.  31
    MARLBS: Team Cooperation Through Bidding.Ron Sun - manuscript
    b>: A cooperative team of agents may perform many tasks better than isolated agents. The question is how coopera-.
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