Intuition insight, imagination and creativity

IEEE Computational Intelligence Magazine

Volumn 2, Issue 3, 2007, Pages 40-52

  Duch, Włodzisław ^a  

^a NICOLAUS COPERNICUS UNIVERSITY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

ABSTRACTING; ALGORITHMS; BRAIN; FEATURE EXTRACTION; LARGE SCALE SYSTEMS; LINGUISTICS; MATHEMATICAL MODELS;

CATEGORIZATION; INTUITION; MYSTERIOUS FEATURES; PARTIAL OBSERVATIONS;

NEURAL NETWORKS;

EID: 34547511103     PISSN: 1556603X     EISSN: None     Source Type: Journal    
DOI: 10.1109/MCI.2007.385365     Document Type: Article

References (65)

1. A. Turing, "Computing Machinery and Intelligence," Mind, vol. 49, pp. 433-460, 1950.
2. IEEE Computational Intelligence Magazine, vol. 1, no. 3, 2006.
3. J.R. Anderson, Learning and memory. Wiley, New York, 2nd Ed, 2000.
4. T. Serre, A. Oliva, and T. Poggio, "A Feedforward Architecture Accounts for Rapid Categorization," Proceedings of the National Academy of Sciences (PNAS), vol. 104, no. 15, pp. 6424-6429, 2007.
5. C. Koch, The Quest for Consciousness: A Neurobiological Approach. Roberts & Company Publishers, Greenwood Village, Co, 2004.
6. W. Duch, "Brain-inspired conscious computing architecture," Journal of Mind and Behavior, vol. 26, no. 1-2, pp. 1-22, 2005.
7. B. Heinrich and T. Bugnyar, "Testing Problem Solving in Ravens: String-Pulling to Reach Food," Ethology, vol. 111, no. 10, pp. 962-976, 2005.
8. R. Wilson and F. Keil, Eds. MIT Encyclopedia of Cognitive Sciences. MIT Press, 1999.
9. M.D. Lieberman, "Intuition: A Social Cognitive Neuroscience Approach," Psychological Bulletin, vol. 126, no. 1, pp. 109-137, 2000.
10. D.G. Myers, Intuition: Its Powers and Perils. Yale University Press, New Haven, CT, 2002.
11. W. Duch, R. Setiono, and J. Zurada, "Computational intelligence methods for understanding of data," Proceedings of the IEEE, vol. 92, no. 5, pp. 771-805, 2004.
12. W. Duch and M. Blachnik, "Fuzzy rule-based systems derived from similarity to prototypes," Lecture Notes in Computer Science, vol. 3316, pp. 912-917, 2004.
13. W. Duch, "Uncertainty of data, fuzzy membership functions, and multi-layer perceptions," IEEE Transactions on Neural Networks, vol. 16, no. 1, pp. 10-23, 2005.
14. W. Duch, "Rules, Similarity, and Threshold Logic," Commentary on E.M. Pothos, The Rules versus Similarity distinction, Behavioral and Brain Sciences, vol. 28, no. 1, pp. 23-23, 2005.
15. K. Grabczewski and W. Duch, "Heterogenous forests of decision trees," Lecture Notes in Computer Science, vol. 2415, pp. 504-509, 2002.
16. H.A. Simon, "Explaining the ineffable: AI on the topics of intuition, insight and inspiration," Proc. 14th Int. Joint. Conference on Artificial Intelligence, vol. 1, pp. 939-948, 1995.
17. A. Linhares, "An Active Symbols Theory of Chess Intuition," Hindu and Machines, vol. 15, no. 2, pp. 131-181, 2005.
18. A. Newel, Unified theories of cognition. Harvard Univ. Press, Cambridge, MA, 1990.
19. J. Hawkins and D. George, "Hierarchical Temporal Memory - Concepts, Theory, and Terminology," Numenta Inc., www.numenta.com, 2006.
20. O.G. Selfrdige and U. Neisser, "Pattern recognition by machine," Scientific American, vol. 203, pp. 60-67, 1960.
21. D.E. Rumelhart and J.L. McClelland (eds), Parallel Distributed Processing, Vol. 1: Foundations, MIT Press, Cambridge, MA, 1986.
22. G.E. Hinton, S. Osindero and Y. The, "A fast learning algorithm for deep belief nets," Neural Computation, vol. 18, pp. 381-414, 2006.
23. W. Duch and G.H.F. Diercksen, "Feature Space Mapping as a universal adaptive system," Computer Physics Communications, vol. 87, pp. 341-371, 1995.
24. R.J. Sternberg, and J.E. Davidson, The nature of insight. MIT Press, Cambridge, MA, 1995.
25. E.A. Feigenbaum and H.A. Simon, "EPAM-like models of recognition and learning," Cognitive Science, vol. 8, pp. 305-336, 1984.
26. H.A. Simon, The sciences of the artificial. 2nd ed, MIT Press, Cambridge, MA, 1981.
27. M. Jung-Beeman, E.M. Bowden, J. Haberman, J.L. Frymiare, S. Arambel-Liu, R. Greenblatt, P.J. Reber, and J. Kounios, "Neural activity when people solve verbal problems with insight," PLoS Biology, vol. 2, no. 4, pp. 500-510, 2004.
28. E.M. Bowden, M. Jung-Beeman, J. Fleck, and J. Kounios, "New approaches to demystifying insight," Trends in Cognitive Science, vol. 9, pp. 322-328, 2005.
29. S. Dehaene, L. Cohen, M. Sigman and F. Vinckier, "The neural code for written words: a proposal," Trends in Cognitive Science, vol. 9, pp. 335-341, 2005.
30. S. Grossberg, "Resonant neural dynamics of speech perception," Journal of Phonetics, vol. 31, pp. 423-445, 2003.
31. F. Pulvermüller, The Neuroscience of signage. On Brain Circuits of Words and Serial. Order. Cambridge, UK: Cambridge University Press, 2003.
32. F. Pulvermüller, "Brain retlections of words and their meaning," Trends in Cognitive Sciences, vol. 5, pp. 517-524, 2001.
33. F. Pulvermüller, "A brain perspective on language mechanisms: From discrete neuronal ensembles to serial order," Progress in Neurobiology, vol. 67, pp. 85-111, 2002.
34. F. Pulvermüller, Y. Shtyrov, and R. Ilmoniemi, "Brain signatures of meaning access in action word recognition," Journal of Cognitive Neuroscience, vol. 17, no. 6, pp. 884-892, 2005.
35. S. Virtue, J. Haberman, Z. Clancy, T. Parrish, and M. Jung-Beeman, "Neural activity of inferences during story comprehension," Brain Research, vol. 1084, pp. 104-114, 2006.
36. K.I. Taylor Monsch, "Semantic Language in the Right Hemisphere: Divided Visual Field and Functional Imaging Studies of Reading," Ph.D. Thesis, University of Zurich, 2002.
37. M.A. Schilling, "A 'Small-World' Network Model of Cognitive Insight," Creativity Research Journal, vol. 17, no. 2-3, pp. 131-154, 2005.
38. F. Crestani, "Application of spreading activation techniques in in-formation retrieval," Artificial Intelligence Review, vol. 11, pp. 453-482, 1997.
39. J.F. Sowa, ed. Principles of Semantic Networks: Explorations in the Representation of Knowledge. Morgan Kaufmann Publishers, San Mateo, CA, 1991.
40. J. Szymanski, T. Sarnatowicz and W. Duch, "Towards avatars with artificial minds: Role of semantic memory," Journal of Ubiquitous Computing and Intelligence, American Scientific Publishers (in print).
41. J. Szymanski and W. Duch, "Semantic Memory Knowledge Acquisition Through Active Dialogues," Proc. of the 20th Int. Joint Conference on Neural Networks (IJCNN), Orlando, IEEE Press, August 2007 (in print).
42. C.D. Manning and H. Schütze, Foundations of Statistical Natural Language Processing. MIT Press, Cambridge, MA, 1999.
43. L. Itert, W. Duch and J. Pestian, "Influence of a priori Knowledge on Medical Document Categorization," IEEE Symposium on Computational Intelligence in Data Mining, IEEE Press, April 2007, pp. 163-170.
44. W. Duch, P. Matykiewicz and J. Pestian, "Neurolinguistic Approach to Vector Representation of Medical Concepts," Proc. of the 20th Int. Joint Conference, on Neural Networks (IJCNN), Orlando, IEEE Press, August 2007 (in print).
45. P. Matykiewicz, W. Duch and J. Pestian, "Nonambiguous Concept Mapping in Medical Domain," Lecture Notes in Artificial Intelligence, vol. 4029, pp. 941-950, 2006.
46. S. Lamb, Pathways of the Brain: The Neurocognitive Basis of Language. Amsterdam & Philadelphia: J. Benjamins Publishing Co. 1999.
47. M. Runco and S. Pritzke, Eds. Encyclopedia of creativity, vol. 1-2, Elsevier, 2005.
48. R.J. Sternberg, Ed. Handbook of Human Creativity. Cambridge: Cambridge University Press, 1998.
49. W. Duch, "Computational creativity," IEEE World Congress on Computational Intelligence, Vancouver, July, 16-21, IEEE Press, pp. 1162-1169, 2006.
50. W. Duch, "Creativity and the Brain," In: A Handbook of Creativity for Teachers. Ed. Ai-Girl Tan, World Scientific Publishing 2007 (in print).
51. W. Duch and M. Pilichowski, "Experiments with computational creativity," Neural Information Processing - Letters and Reviews, vol. 11, no. 3, March 2007 (in print).
52. S.A. Mednick, "The associative basis of the creative process," Psychological Review, vol. 69, pp. 220-232, 1962.
53. K.M. Heilman, S.E. Nadeau and D.O. Beversdorf, "Creative innovation: Possible brain mechanism," Neurocase, vol. 9, pp. 369-379, 2003.
54. T.P. McNamara, Semantic Priming. Perspectives from Memory and Word Recognition. Psychology Press, New York, 2005.
55. A. Gruszka and E. Nȩcka, "Priming and Acceptance of Close and Remote Associations by Creative and Less Creative People," Creativity Research Journal, vol. 14, no. 2, pp. 193-205, 2002.
56. T. Wellens, V. Shatokhin, and A. Buchleitner, "Stochastic resonance," Reports on Progress in Physics, vol. 67, pp. 45-105, 2004.
57. R.M. Warren and R.P. Warren, "Auditory illusions and confusions," Scientific American, vol. 223, pp. 30-36, 1970.
58. D.S. Ruchkin, J. Grafman, K. Cameron, and R.S. Berndt, "Working Memory Retention Systems: A State of Activated Long-Term Memory," Behavioral and Brain Sciences, vol. 26, no. 6, pp. 709-728, 2003.
59. D.R. Hofstadter, Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Triought. NY: Basic Books, 1995.
60. J. Rehling, Letter Spirit (Part Two): Modeling Creativity in a Visual Domain. PhD Thesis, Indiana University, 2001.
61. T. Kohonen, Correlation matrix memories, IEEE Transactions on Computers C, vol. 21, pp. 353-359, 1972.
62. H. Damasio, T.J. Grabowski, D. Tranel, R.D. Hichwa, and A.R. Damasio, "A neural basis for lexical retrieval," Nature, vol. 380, pp. 499-505, 1996.
63. A. Martin, C.L. Wiggs, L.G. Ungerleider and J.V. Haxby, "Neural correlates of category-specific knowledge," Nature, vol. 379, pp. 649-652, 1996.
64. W. Duch, "Platonic model of mind as an approximation to neurodynamics," In: Brain-like computing and intelligent information systems, ed. S-i. Amari, N. Kasabov, Springer, Singapore, Chap. 20, pp. 491-512, 1997.
65. W. Duch, "Categorization, Prototype Theory and Neural Dynamics," Proc. of the 4th International Coherence on Soft Computing'96, Iizuka, Japan, ed. T. Yamakawa and. G. Matsumoto, pp. 482-485, 1996.