Incubation, insight, and creative problem solving: a unified theory and a connectionist model.

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 tasks, (c) the redundant representation of explicit and implicit knowledge, (d) the integration of the results of explicit and implicit processing, and (e) the iterative (and possibly bidirectional) processing. A computational implementation of the theory is developed based on the CLARION cognitive architecture and applied to the simulation of relevant human data. This work represents an initial step in the development of process-based theories of creativity encompassing incubation, insight, and various other related phenomena.

[1]  Steven M. Smith,et al.  The creative cognition approach. , 1995 .

[2]  R. Likert “Technique for the Measurement of Attitudes, A” , 2022, The SAGE Encyclopedia of Research Design.

[3]  R. Schank,et al.  Making Machines Creative , 1995 .

[4]  R. Woodworth Archives of psychology , 2010 .

[5]  Don Steinberg,et al.  Deductive reasoning , 1989 .

[6]  Christopher Y. Olivola,et al.  Doing Unto Future Selves As You Would Do Unto Others: Psychological Distance and Decision Making , 2008, Personality & social psychology bulletin.

[7]  Tim Curran,et al.  Attentional and Nonattentional Forms of Sequence Learning , 1993 .

[8]  R. Mayer The search for insight: Grappling with gestalt psychology''s unanswered questions , 1995 .

[9]  G. Bower The Psychology of Learning and Motivation , 2021, Psychology of Learning and Motivation.

[10]  Kevin M. Brooks,et al.  Thoughts beyond words : When language overshadows insight , 1993 .

[11]  Daniel B. Willingham,et al.  On the development of procedural knowledge. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[12]  J. Glover,et al.  Handbook of creativity. , 1989 .

[13]  R. Radner,et al.  Decision and Organization. A Volume in Honor of Jacob Marschak. Edited by C.B. Mc Guire and Roy Radner. Studies in Mathematical and Managerial Economics, volume 12. Amsterdam, London, North-Holland Publishing Company, 1972 X p. 361 p., fl. 63.00. , 1973, Recherches économiques de Louvain.

[14]  J. Fodor,et al.  Connectionism and cognitive architecture: A critical analysis , 1988, Cognition.

[15]  B. H. Cohen Recall of categorized words lists. , 1963 .

[16]  Anders Krogh,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[17]  R. Mathews,et al.  Role of Implicit and Explicit Processes in Learning From Examples : A Synergistic Effect , 2004 .

[18]  Axel Cleeremans,et al.  Implicit learning: news from the front , 1998, Trends in Cognitive Sciences.

[19]  Shawn Okuda Sakamoto,et al.  Handbook of Creativity: Experimental Studies of Creativity , 1998 .

[20]  J. Hadamard,et al.  The Psychology of Invention in the Mathematical Field. , 1945 .

[21]  R. Mayer Handbook of Creativity: Fifty Years of Creativity Research , 1998 .

[22]  R. Sun On Variable Binding in Connectionist Networks , 1992 .

[23]  J. Tenenbaum,et al.  Generalization, similarity, and Bayesian inference. , 2001, The Behavioral and brain sciences.

[24]  C. Sumiyoshi CATEGORY BASED INDUCTION , 1997 .

[25]  Steven M. Smith Fixation, incubation, and insight in memory and creative thinking. , 1995 .

[26]  Timothy D. Wilson,et al.  Thinking too much: introspection can reduce the quality of preferences and decisions. , 1991, Journal of personality and social psychology.

[27]  Evan Heit,et al.  A Bayesian Analysis of Some Forms of Inductive Reasoning , 1998 .

[28]  Stellan Ohlsson,et al.  Deep Learning - How the Mind Overrides Experience , 2011 .

[29]  Richard Alterman,et al.  Adaptive Planning , 1988, Cogn. Sci..

[30]  C. Lebiere,et al.  The Atomic Components of Thought , 1998 .

[31]  Steven M. Smith,et al.  Creative Cognition: Theory, Research, and Applications , 1996 .

[32]  Ron Sun,et al.  Duality of the mind - a bottom-up approach toward cognition , 2001 .

[33]  R. Sternberg Handbook of Creativity: Subject Index , 1998 .

[34]  Natalia Derbentseva,et al.  Insight in Problem Solving , 2009 .

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

[36]  Teresa M. Amabile,et al.  ? + ? = creativity. , 2018, Public health nursing.

[37]  Franz Emanuel Weinert,et al.  Memory performance and competencies : issues in growth and development , 1995 .

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

[39]  G. Regehr,et al.  Intuition in the context of discovery , 1990, Cognitive Psychology.

[40]  R. Mathews,et al.  Insight without Awareness: On the Interaction of Verbalization, Instruction and Practice in a Simulated Process Control Task , 1989 .

[41]  Edward E. Smith,et al.  The Case for Rules in Reasoning , 1992, Cogn. Sci..

[42]  N. Maier Reasoning in humans. II. The solution of a problem and its appearance in consciousness. , 1931 .

[43]  H. Simon,et al.  The Processes of Creative Thinking , 1959 .

[44]  G. Logan Toward an instance theory of automatization. , 1988 .

[45]  M. Scheerer,et al.  Problem Solving , 1967, Nature.

[46]  Robert Proulx,et al.  NDRAM: nonlinear dynamic recurrent associative memory for learning bipolar and nonbipolar correlated patterns , 2005, IEEE Transactions on Neural Networks.

[47]  Carol A. Seger,et al.  Implicit learning. , 1994, Psychological bulletin.

[48]  S. Mednick The associative basis of the creative process. , 1962, Psychological review.

[49]  S. Ohlsson Information-processing explanations of insight and related phenomena , 1992 .

[50]  J. Metcalfe,et al.  Metacognition : knowing about knowing , 1994 .

[51]  C. Martindale Creativity and connectionism. , 1995 .

[52]  John F. Kihlstrom,et al.  Intuition, incubation, and insight: Implicit cognition in problem solving. , 1996 .

[53]  P. Smolensky On the proper treatment of connectionism , 1988, Behavioral and Brain Sciences.

[54]  J. Metcalfe Feeling of knowing in memory and problem solving. , 1986 .

[55]  Derek Partridge,et al.  Creativity: a survey of AI approaches , 1993, Artificial Intelligence Review.

[56]  Z. Dienes,et al.  Implicit learning: Below the subjective threshold , 1997 .

[57]  M. Ashcraft Human memory and cognition , 1989 .

[58]  L. Brooks,et al.  Specializing the operation of an explicit rule , 1991 .

[59]  Jonathan Evans Dual-processing accounts of reasoning, judgment, and social cognition. , 2008, Annual review of psychology.

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

[61]  S. Hélie Implicit cognition in problem solving , 2012 .

[62]  W. Köhler The Mentality of Apes. , 2018, Nature.

[63]  J. Metcalfe,et al.  Intuition in insight and noninsight problem solving , 1987, Memory & cognition.

[64]  Matthew I. Isaak,et al.  Constraints on thinking in insight and invention. , 1995 .

[65]  N. Jausovec,et al.  What Can Heart Rate Tell Us About the Creative Process , 1995 .

[66]  Melanie Mitchell,et al.  The Copycat project: a model of mental fluidity and analogy-making , 1995 .

[67]  D E Meyer,et al.  Activation and metacognition of inaccessible stored information: potential bases for incubation effects in problem solving. , 1987, Journal of experimental psychology. Learning, memory, and cognition.

[68]  Sébastien Hélie,et al.  Automaticity in rule-based and information-integration categorization , 2010, Attention, perception & psychophysics.

[69]  Xi Zhang,et al.  Accounting for a variety of reasoning data within a cognitive architecture , 2006, J. Exp. Theor. Artif. Intell..

[70]  Steven M. Smith,et al.  The Use of Environmental Clues During Incubation , 2002 .

[71]  J. Pearl Causality: Models, Reasoning and Inference , 2000 .

[72]  J. von Neumann,et al.  Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components , 1956 .

[73]  Jonathan Evans On the resolution of conflict in dual process theories of reasoning , 2007 .

[74]  S. Sloman The empirical case for two systems of reasoning. , 1996 .

[75]  T. Lubart Models of the Creative Process: Past, Present and Future , 2001 .

[76]  R. Sun,et al.  The interaction of the explicit and the implicit in skill learning: a dual-process approach. , 2005, Psychological review.

[77]  Z. Dienes,et al.  A theory of implicit and explicit knowledge , 1999, Behavioral and Brain Sciences.

[78]  F. Durso,et al.  Graph-Theoretic Confirmation of Restructuring During Insight , 1994 .

[79]  L. Schauble,et al.  Beyond Modularity: A Developmental Perspective on Cognitive Science. , 1994 .

[80]  J. O. Urmson,et al.  The William James Lectures , 1963 .

[81]  Teuvo Kohonen,et al.  Correlation Matrix Memories , 1972, IEEE Transactions on Computers.

[82]  A. Reber Implicit learning and tacit knowledge , 1993 .

[83]  Tao Xiong,et al.  A combined SVM and LDA approach for classification , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[84]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[85]  Ron Sun,et al.  Autonomous learning of sequential tasks: experiments and analyses , 1998, IEEE Trans. Neural Networks.

[86]  A. Reber,et al.  Implicit learning: An analysis of the form and structure of a body of tacit knowledge , 1977, Cognition.

[87]  F. Craik,et al.  Depth of processing and the retention of words , 1975 .

[88]  L. Lunsky Contemporary Approaches to Creative Thinking. , 1963 .

[89]  Edward M. Bowden,et al.  New approaches to demystifying insight , 2005, Trends in Cognitive Sciences.

[90]  Mark T. Keane,et al.  Advances in the psychology of thinking , 1992 .

[91]  Daniel B. Willingham,et al.  A Neuropsychological Theory of Motor Skill Learning , 2004 .

[92]  J. Hadamard,et al.  The Psychology of Invention in the Mathematical Field. , 1945 .

[93]  F. Ashby,et al.  The effects of concurrent task interference on category learning: Evidence for multiple category learning systems , 2001, Psychonomic bulletin & review.

[95]  D. Campbell Blind variation and selective retention in creative thought as in other knowledge processes. , 1960, Psychological review.

[96]  Wlodzislaw Duch,et al.  Computational Creativity , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[97]  Lotfi A. Zadeh,et al.  Fuzzy Logic , 2009, Encyclopedia of Complexity and Systems Science.

[98]  P N Johnson-Laird,et al.  Deductive reasoning. , 1999, Annual review of psychology.

[99]  Sébastien Hélie,et al.  Energy minimization in the nonlinear dynamic recurrent associative memory , 2008, Neural Networks.

[100]  J. Schooler,et al.  The ineffability of insight. , 1995 .

[101]  John R. Anderson,et al.  Human memory: An adaptive perspective. , 1989 .

[102]  T. Greenhalgh,et al.  Intuition , 2002, BMJ : British Medical Journal.

[103]  Xi Zhang,et al.  Modeling meta-cognition in a cognitive architecture , 2006, Cognitive Systems Research.

[104]  D. Broadbent,et al.  Interactive tasks and the implicit‐explicit distinction , 1988 .

[105]  H. Simon,et al.  Scientific Discovery and the Psychology of Problem Solving , 1977 .

[106]  Ron Sun,et al.  Integrating rules and connectionism for robust commonsense reasoning , 1994, Sixth-generation computer technology series.

[107]  J. Hayes Cognitive Processes in Creativity , 1989 .

[108]  Stephen A. Ritz,et al.  Distinctive features, categorical perception, and probability learning: some applications of a neural model , 1977 .

[109]  John R. Anderson,et al.  The Adaptive Nature of Human Categorization , 1991 .

[110]  J. J. Hopfield,et al.  “Neural” computation of decisions in optimization problems , 1985, Biological Cybernetics.

[111]  L. Rips The Psychology of Proof: Deductive Reasoning in Human Thinking , 1994 .

[112]  Melissa A. Schilling A "Small-World" Network Model of Cognitive Insight , 2005 .

[113]  N. Chater,et al.  Rational models of cognition , 1998 .

[114]  Terri Gullickson The Creative Mind: Myths and Mechanisms. , 1995 .

[115]  BART KOSKO,et al.  Bidirectional associative memories , 1988, IEEE Trans. Syst. Man Cybern..

[116]  Francis T. Durso,et al.  Network Structures in Proximity Data , 1989 .

[117]  Sébastien Hélie,et al.  A neurocomputational model of automaticity and maintenance of abstract rules , 2009, 2009 International Joint Conference on Neural Networks.

[118]  R. Sternberg RETRACTED ARTICLE: The Nature of Creativity , 2006 .

[119]  Steven M. Smith,et al.  Incubated reminiscence effects , 1991, Memory & cognition.

[120]  Rick B. van Baaren,et al.  On Making the Right Choice: The Deliberation-Without-Attention Effect , 2006, Science.

[121]  P. Johnson-Laird Freedom and constraint in creativity. , 1988 .

[122]  Richard Reviewer-Granger Unified Theories of Cognition , 1991, Journal of Cognitive Neuroscience.

[123]  S. Hélie Mixed Effects of Distractor Tasks on Incubation , 2008 .

[124]  Jonathan Evans The heuristic-analytic theory of reasoning: Extension and evaluation , 2006, Psychonomic bulletin & review.

[125]  M. Boden The creative mind : myths & mechanisms , 1991 .

[126]  B. H. Cohen,et al.  RECALL OF CATEGORIZED WORD LISTS. , 1963, Journal of Experimental Psychology.

[127]  D. Gentner,et al.  Structure mapping in analogy and similarity. , 1997 .

[128]  Wei Ji Ma,et al.  Bayesian inference with probabilistic population codes , 2006, Nature Neuroscience.

[129]  G. Logan Shapes of reaction-time distributions and shapes of learning curves: a test of the instance theory of automaticity. , 1992, Journal of experimental psychology. Learning, memory, and cognition.

[130]  Randolph M. Jones,et al.  A computational model of scientific insight , 1986 .

[131]  Guy Lories,et al.  Confidence Level and Feeling of Knowing in Question Answering - the Weight of Inferential Processes , 1992 .

[132]  R. Bruce Lindsay,et al.  Mind and Cosmos: Essays in Contemporary Science and Philosophy , 1967 .

[133]  Todd R. Johnson,et al.  Use of current explanations in multicausal abductive reasoning , 2001, Cogn. Sci..

[134]  Margaret A. Boden,et al.  The Creative Mind - Myths and Mechanisms (2. ed.) , 2003 .

[135]  Eliot R. Smith,et al.  Dual-Process Models in Social and Cognitive Psychology: Conceptual Integration and Links to Underlying Memory Systems , 2000 .

[136]  Roni Reiter-Palmon,et al.  Encyclopedia of Creativity , 2011 .

[137]  B. Libet Unconscious cerebral initiative and the role of conscious will in voluntary action , 1985, Behavioral and Brain Sciences.

[138]  Serge Larochelle,et al.  The origin of exemplar effects in rule-driven categorization. , 2005, Journal of experimental psychology. Learning, memory, and cognition.

[139]  Jonathan Evans,et al.  Logic and human reasoning: an assessment of the deduction paradigm. , 2002, Psychological bulletin.

[140]  A. Dietrich,et al.  The cognitive neuroscience of creativity , 2004, Psychonomic bulletin & review.