Architektury kognitywne, czyli jak zbudować sztuczny umysł

Architektury kognitywne (AK) są próbą stworzenia modeli komputerowych integrujących wiedzę o działaniu umysłu. Ich zadaniem jest implementacja konkretnych schematów działania funkcji poznawczych umożliwiająca testowanie tych funkcji na szerokiej gamie zagadnień. Wiele architektur kognitywnych opracowano w celu symulacji procesu komunikacji pomiędzy człowiekiem i złożonymi maszynami (HCI, Human-Computer Interfaces), symulowania czasów reakcji oraz różnych psychofizycznych zależności. Można to do pewnego stopnia osiągnąć budując modele układu poznawczego na poziomie symbolicznym, z wiedzą w postaci reguł logicznych. Istnieją też projekty, które próbują powiązać procesy poznawcze z aktywacją modułów reprezentujących konkretne obszary mózgu, zgodnie z obserwacjami w eksperymentach z funkcjonalnym rezonansem magnetycznym (fMRI). Dużą grupę stanowią architektury oparte na podejściu logicznym, które mają na celu symulację wyższych czynności poznawczych, przede wszystkim procesów myślenia i rozumowania. Niektóre z projektów rozwoju architektur poznawczych skupiają większe grupy badawcze działające od wielu dziesięcioleci.

[1]  Robert Hecht-Nielsen.  Confabulation theory - the mechanism of thought , 2007 .

[2]  Wlodzislaw Duch.  From cognitive models to neurofuzzy systems—the mind space approach , 1996 .

[3]  Pat Langley,et al.  Learning Recursive Control Programs from Problem Solving , 2006, J. Mach. Learn. Res..

[4]  C. Lebiere,et al.  The Newell Test for a theory of cognition , 2003, Behavioral and Brain Sciences.

[5]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[6]  E. Korner,et al.  Cortical architecture and self-referential control for brain-like computation , 2002, IEEE Engineering in Medicine and Biology Magazine.

[7]  Edward A. Feigenbaum,et al.  Some challenges and grand challenges for computational intelligence , 2003, JACM.

[8]  A. Antunes.  Democracia e Cidadania na Escola: Do Discurso à Prática , 2008 .

[9]  Stan Franklin,et al.  THE LIDA ARCHITECTURE: ADDING NEW MODES OF LEARNING TO AN INTELLIGENT, AUTONOMOUS, SOFTWARE AGENT , 2006 .

[10]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[11]  Wlodzislaw Duch,et al.  Towards Understanding of Natural Language: Neurocognitive Inspirations , 2007, ICANN.

[12]  James L. McClelland,et al.  James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.

[13]  B. Kokinov,et al.  TOWARDS ACTIVE VISION IN THE DUAL COGNITIVE ARCHITECTURE , 2006 .

[14]  Giulio Sandini,et al.  A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents , 2007, IEEE Transactions on Evolutionary Computation.

[15]  Pat Langley,et al.  An Adaptive Architecture for Physical Agents , 2005, Web Intelligence.

[16]  Kevin A. Gluck,et al.  Modeling Human Behavior With Integrated Cognitive Architectures : Comparison, Evaluation, and Validation , 2006 .

[17]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[18]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[19]  Ron Sun,et al.  From implicit skills to explicit knowledge: a bottom-up model of skill learning , 2001, Cogn. Sci..

[20]  Bradford Z. Mahon,et al.  A critical look at the embodied cognition hypothesis and a new proposal for grounding conceptual content , 2008, Journal of Physiology-Paris.

[21]  Nils J. Nilsson,et al.  Human-Level Artificial Intelligence? Be Serious! , 2005, AI Mag..

[22]  James A. Anderson,et al.  Programming a Parallel Computer: The Ersatz Brain Project , 2007, Challenges for Computational Intelligence.

[23]  Ben Goertzel,et al.  An Integrative Methodology for Teaching Embodied Non-Linguistic Agents, Applied to Virtual Animals in Second Life , 2008, AGI.

[24]  M. Shanahan.  A cognitive architecture that combines internal simulation with a global workspace , 2006, Consciousness and Cognition.

[25]  Patrick Henry Winston,et al.  The psychology of computer vision , 1976, Pattern Recognit..

[26]  Wlodzislaw Duch.  Brain-Inspired Conscious Computing Architecture , 2005 .

[27]  Włodzisław Duch,et al.  Towards Avatars with Artificial Minds: Role of Semantic Memory , 2007 .

[28]  Jonathan D. Cohen,et al.  A Biologically Based Computational Model of Working Memory , 1999 .

[29]  H. Gardner.  Multiple intelligences : the theory in practice , 1993 .

[30]  Friedemann Pulvermüller,et al.  The Neuroscience of Language: On Brain Circuits of Words and Serial Order , 2003 .

[31]  E. Feigenbaum,et al.  Computers and Thought , 1963 .

[32]  Tetsuya Hoya.  Artificial Mind System - Kernel Memory Approach , 2005, Studies in Computational Intelligence.

[33]  Saso Dzeroski,et al.  Inductive Logic Programming: Techniques and Applications , 1993 .

[34]  Rodney A. Brooks,et al.  Building brains for bodies , 1995, Auton. Robots.

[35]  Xi Zhang,et al.  Top-down versus bottom-up learning in cognitive skill acquisition , 2004, Cognitive Systems Research.

[36]  Wlodzislaw Duch,et al.  Cognitive Architectures: Where do we go from here? , 2008, AGI.

[37]  W. Duch,et al.  Intuition, Insight, Imagination and Creativity , 2007, IEEE Computational Intelligence Magazine.

[38]  M. Just,et al.  From the Selectedworks of Marcel Adam Just the Organization of Thinking: What Functional Brain Imaging Reveals about the Neuroarchitecture of Complex Cognition , 2022 .

[39]  John E. Laird,et al.  Extending the Soar Cognitive Architecture , 2008, AGI.

[40]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[41]  Stuart C. Shapiro,et al.  Metacognition in SNePS , 2007, AI Mag..

[42]  L. Shastri,et al.  From simple associations to systematic reasoning: A connectionist representation of rules, variables and dynamic bindings using temporal synchrony , 1993, Behavioral and Brain Sciences.

[43]  Michael J. Witbrock,et al.  Common Sense Reasoning - From Cyc to Intelligent Assistant , 2006, Ambient Intelligence in Everyday.

[44]  Rodney A. Brooks,et al.  Elephants don't play chess , 1990, Robotics Auton. Syst..

[45]  Wlodzislaw Duch,et al.  Towards Comprehensive Foundations of Computational Intelligence , 2007, Challenges for Computational Intelligence.

[46]  Maciej Pilichowski,et al.  Experiments with Computational Creativity , 2007 .

[47]  G. Edelman.  Neural Darwinism: Selection and reentrant signaling in higher brain function , 1993, Neuron.

[48]  John R. Anderson.  How Can the Human Mind Occur in the Physical Universe , 2007 .

[49]  W lodzis,et al.  A SOLUTION TO FUNDAMENTAL PROBLEMS OF COGNITIVE SCIENCES , 2007 .

[50]  Jonathan Freeman,et al.  Computing Machinery and the Individual: the Personal Turing Test , 2005 .

[51]  Juyang Weng,et al.  From neural networks to the brain: autonomous mental development , 2006, IEEE Computational Intelligence Magazine.

[52]  Rene J. de Pontbriand,et al.  Modeling Human Behavior with Integrated Cognitive Architectures: Comparison, Evaluation, and Validation Edited by Kevin A. Gluck & Richard A. Pew 2005, 440 pages, $55.00 Mahwah, NJ: Lawrence Erlbaum Associates ISBN 0-8058-5048-1 , 2007 .

[53]  Allen Newell,et al.  Computer science as empirical inquiry: symbols and search , 1976, CACM.

[54]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .

[55]  D E Kieras,et al.  A computational theory of executive cognitive processes and multiple-task performance: Part 1. Basic mechanisms. , 1997, Psychological review.

[56]  Nicholas L. Cassimatis.  Adaptive Algorithmic Hybrids for Human-Level Artificial Intelligence , 2006, AGI.

[57]  De Vries.  Book review: R.C. O'Reilly and Y. Munakata: Computational explorations in cognitive neuroscience: understanding the mind by stimulating the brain. Cambridge, Mass: The MIT Press. , 2002 .

[58]  R. O’Reilly,et al.  Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain , 2000 .

[59]  M. Sigman,et al.  Opinion TRENDS in Cognitive Sciences Vol.9 No.7 July 2005 The neural code for written words: a proposal , 2022 .

[60]  Wlodzislaw Duch,et al.  A new methodology of extraction, optimization and application of crisp and fuzzy logical rules , 2001, IEEE Trans. Neural Networks.

[61]  Tom Michael Mitchell,et al.  Explanation-based generalization: A unifying view , 1986 .

[62]  B. Baars.  A cognitive theory of consciousness , 1988 .

[63]  David E. Kieras,et al.  Modeling with Perceptual and Memory Constraints: An EPIC-Soar Model of a Simplified Enroute Air Traffic Control Task , 2001 .

[64]  Robert James Firby,et al.  Adaptive execution in complex dynamic worlds , 1989 .

[65]  O. Silva.  Pathways of the brain: The neurocognitive basis of language , 2000 .

[66]  M. Meeter,et al.  Tracelink: A model of consolidation and amnesia , 2005, Cognitive neuropsychology.

[67]  Allen Newell,et al.  GPS, a program that simulates human thought , 1995 .

[68]  M. Minsky.  The Society of Mind , 1986 .

[69]  S. Lamb.  Pathways of the brain , 1999 .

[70]  L. Barsalou.  Grounding Symbolic Operations in the Brain's Modal Systems , 2008 .

[71]  A. Newell.  Unified Theories of Cognition , 1990 .

[72]  Norbert Jankowski,et al.  Versatile and Efficient Meta-Learning Architecture: Knowledge Representation and Management in Computational Intelligence , 2007, 2007 IEEE Symposium on Computational Intelligence and Data Mining.

[73]  Pei Wang,et al.  Rigid Flexibility: The Logic of Intelligence , 2006 .

[74]  W. Duch,et al.  Challenges for Computational Intelligence (Duch, W. and Mandziuk, J., Eds.; 2007) [Book reviews] , 2009, IEEE Transactions on Neural Networks.

[75]  B. Goertzel.  The Hidden Pattern: A Patternist Philosophy of Mind , 2006 .

[76]  Max Coltheart,et al.  Cognitive Neuropsychology , 2014, Scholarpedia.

[77]  Włodzisław Duch,et al.  Quo vadis, computational intelligence? , 2004 .

[78]  Pentti O. A. Haikonen.  Robot Brains: Circuits and Systems for Conscious Machines , 2007 .