Results for 'Ron Sun Todd Peterson'

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  1. A Subsymbolic Symbolic Model for Learning Sequential Navigation.Ron Sun Todd Peterson - unknown
    To deal with reactive sequential decision tasks we present a learning model Clarion which is a hybrid connectionist model consisting of both localist and dis tributed representations based on the two level ap proach proposed in Sun The model learns and utilizes procedural and declarative knowledge tapping into the synergy of the two types of processes It uni es neural reinforcement and symbolic methods to perform on line bottom up learning Experiments in various situations are reported that shed light on (...)
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  2. 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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  3. 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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  4. 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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  5. 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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  6. EMAIL: [email protected]Ron Sun & Todd Peterson - unknown
    In developing autonomous agents, one usually emphasizes only (situated) procedural knowledge, ignoring more explicit declarative knowledge. On the other hand, in developing symbolic reasoning models, one usually emphasizes only declarative knowledge, ignoring procedural knowledge. In contrast, we have developed a learning model Clarion, which is a hybrid connectionist model consisting of both localist and distributed representations, based on the two-level approach proposed in Sun (1995). learns and utilizes both procedural and declarative knowledge, tapping into the synergy of..
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  7. Tuscaloosa, AL 35487.Todd Peterson, Ron Sun & Edward Merrill - unknown
    This paper introduces a hybrid model that combines connectionist, symbolic, and reinforcement learning for tackling reactive sequential decision tasks by a situated agent. Both procedural skills and high-level symbolic representations are acquired through an agent's experience interacting with the world, in a bottom-up direction. It deals with on-line learning, that is, learning continuously from on-going experience in the world, without the use of preconstructed data sets or preconceived concepts. The model is a connectionist one based on a two-level approach proposed (...)
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  8. Autonomous Learning of Sequential Tasks: Experiments and Analyses.Todd Peterson - unknown
    This paper presents a novel learning model Clarion , which is a hybrid model based on the two-level approach proposed in Sun (1995). The model integrates neural, reinforcement, and symbolic learning methods to perform on-line, bottom-up learning (i.e., learning that goes from neural to symbolic representations). The model utilizes both procedural and declarative knowledge (in neural and symbolic representations respectively), tapping into the synergy of the two types of processes. It was applied to deal with sequential decision tasks. Experiments and (...)
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  9.  80
    Moscow Nights.Ron Wilburn, Todd Jones & David Beisecker - 2001 - The Philosophers' Magazine 15 (15):30-31.
  10. Cambridge Handbook of Computational Psychology-by Ron Sun [Editor].Robert L. West - 2009 - Journal of Mind and Behavior 30 (4):337.
     
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  11.  89
    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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  12. 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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  13.  62
    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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  14.  92
    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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  15.  38
    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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  16.  12
    Incubation, Insight, and Creative Problem Solving: A Unified Theory and a Connectionist Model.Sébastien Hélie & Ron Sun - 2010 - Psychological Review 117 (3):994-1024.
  17.  59
    On Levels of Cognitive Modeling.Ron Sun, L. Andrew Coward & Michael J. Zenzen - 2005 - Philosophical Psychology 18 (5):613-637.
  18. 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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  19. 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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  20.  1
    Robust Reasoning: Integrating Rule-Based and Similarity-Based Reasoning.Ron Sun - 1995 - Artificial Intelligence 75 (2):241-295.
  21. 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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  22.  1
    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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  23.  5
    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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  24. 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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  25.  74
    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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  26.  91
    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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  27. 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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  28. 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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  29. 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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  30.  41
    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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  31. Introduction to Computational Cognitive Modeling.Ron Sun - 2008 - In The Cambridge Handbook of Computational Psychology. Cambridge University Press. pp. 3--19.
     
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  32. 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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  33.  48
    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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  34. Proceedings of the 28th Annual Conference of the Cognitive Science Society.Ron Sun & Naomi Miyake (eds.) - 2006 - CPC Press.
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  35.  5
    Experiences and Learnings From Induced Seismicity Regulation in Alberta.Todd Shipman, Ron MacDonald & Tom Byrnes - 2018 - Interpretation: SEG 6 (2):SE15-SE21.
    We have examined the experiences and learnings acquired through the implementation of the Alberta Energy Regulator’s subsurface order no. 2 traffic light protocol. On 22 January 2015, a 4.4 [Formula: see text] seismic event occurred near a hydraulic fracturing operation in west-central Alberta and was felt by residents of the town of Fox Creek. On 19 February 2015, the AER issued sub or no. 2 to help manage induced seismicity, as related to hydraulic fracturing of the Duvernay zone in a (...)
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  36. 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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  37. 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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  38. 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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  39.  81
    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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  40. 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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  41. 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.
  42.  41
    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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  43. Anatomy of Mind: Exploring Psychological Mechanisms & Processes, Clarion Cognitive Architecture.Ron Sun - 2016 - Oxford University Press 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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  44.  6
    Modeling Emotion Contagion Within a Computational Cognitive Architecture.Ron Sun, Joseph Allen & Eric Werbin - 2022 - Journal of Cognition and Culture 22 (1-2):60-89.
    The issue of emotion contagion has been gaining attention. Humans can share emotions, for example, through gestures, through speech, or even through online text via social media. There have been computational models trying to capture emotion contagion. However, these models are limited as they tend to represent agents in a very simplified way. There exist also more complex models of agents and their emotions, but they are not yet addressing emotion contagion. We use a more psychologically realistic and better validated (...)
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  45. 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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  46. 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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  47.  12
    After Empire: The Art and Ethos of Enduring Peace; Religion, Politics, and the Christian Right: Post 9/11 Powers and American Empire. [REVIEW]Rebecca Todd Peterson - 2007 - Journal of the Society of Christian Ethics 27 (1):310-313.
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  48. Accessibility Versus Action-Centeredness in the Representation of Cognitive Skills.Ron Sun & Xi Zhang - unknown
    We believe that the distinction between procedural and declarative knowledge unnecessarily confounds two issues: action-centeredness and accessibility, and can be made clearer through separating the two aspects. The work presents an integrated model of skill learning that takes into account both implicit and explicit processes and both action-centered and non-action-centered knowledge. We examine and simulate human data in the Letter Counting task. The work shows how the data may be captured using either the action-centered knowledge alone or the combined action-centered (...)
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  49. 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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  50. Cognitive Social Simulation Incorporating Cognitive Architectures.Ron Sun - unknown
    Agent-based social simulation (with multi-agent systems), which is an important aspect of social computing, can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents and therefore their social interactions. A cognitive architecture is a domain-generic computational cognitive model that may be used for a broad multiple-domain analysis of individual behavior. In this article, an example of a cognitive architecture is given, and its applications to social simulation described. Some challenging issues in this regard are (...)
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