Foundations of Intelligence Science
Author(s)
Zhongzhi Shi
ABSTRACT
In order to make significant progress toward achievement of human level machine intelligence a paradigm shift is needed. More specifically, the natural intelligence and artificial intelligence should be closely interacted in Intelligence Science study, instead of separate from each other. In order to reach the paradigm, brain science, cognitive science, artificial intelligence and others should cross-research together. Brain science explores the essence of brain, research on the principle and model of natural intelligence in molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. Artificial intelligence attempts simulation, extension and expansion of human intelligence using artificial methodology and technology. All together pursue to explore the mechanism and principle of intelligence which is the engine of advanced science and technology. The paper will give the definition of intelligence and discuss ten big issues of Intelligence Science. The conclusion and perspective will be given in last section.
In order to make significant progress toward achievement of human level machine intelligence a paradigm shift is needed. More specifically, the natural intelligence and artificial intelligence should be closely interacted in Intelligence Science study, instead of separate from each other. In order to reach the paradigm, brain science, cognitive science, artificial intelligence and others should cross-research together. Brain science explores the essence of brain, research on the principle and model of natural intelligence in molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. Artificial intelligence attempts simulation, extension and expansion of human intelligence using artificial methodology and technology. All together pursue to explore the mechanism and principle of intelligence which is the engine of advanced science and technology. The paper will give the definition of intelligence and discuss ten big issues of Intelligence Science. The conclusion and perspective will be given in last section.
Cite this paper
nullZ. Shi, "Foundations of Intelligence Science," International Journal of Intelligence Science, Vol. 1 No. 1, 2011, pp. 8-16. doi: 10.4236/ijis.2011.11002.
nullZ. Shi, "Foundations of Intelligence Science," International Journal of Intelligence Science, Vol. 1 No. 1, 2011, pp. 8-16. doi: 10.4236/ijis.2011.11002.
References
[1] J. McCarthy, “The Future of AI-A Manifesto,” AI Magazine, Vol. 26, No. 4, 2005, p. 39. [2] H. Jeff and S. Blakeslee, “On Intelligence, Times Books,” Henry Holt and Company, New York City, 2004. [3] R. Granger, “Engines of the Brain,” AI Magazine, Vol. 27, No. 2, 2006, pp. 15-31. [4] P. Langley, “Cognitive Architectures and General Intelligent Systems,” AI Magazine, Vol. 27, No. 2, 2006, pp. 33-44, [5] K. Sycara, “Multi-Agent Systems,” AI Magazine, Vol. 19, No. 2, 1998, pp. 79-93. [6] N. Cassimatis, “A Cognitive Substrate for Achieving Human-Level Intelligence,” AI Magazine, Vol. 27, No. 2, 2006, pp. 45-56. [7] J. Snaider, R. McCall, S. Franklin, “The LIDA Framework as a General Tool for AGI,” AGI2011. (To be appeared). [8] Intelligence Science Web http://www.intsci.ac.cn/. [9] Z. Z. Shi, “Intelligence Sci-ence,” in Chinese, Tsinghua University Press, Beijing, 2006. [10] Z. Z. Shi, “Artificial Thought and Intelligent Sys-tems,” AI Summer School’94, Beijing, 1994. [11] S. Legg and M. Hutter, “A Collection of Definitions of Intelligence,” 2006. www.vetta.org/shane/intelligence.html. [12] M. F. Bear, B. Connors, M. Paradiso, M. F. Bear, B. W. Connors and M. A. Neuroscience, “Exploring the Brain,” 2nd Edition, Lippincott Williams & Wilkins, Philadelphia 2002. [13] H. Z. Shouval, “Models of Synaptic Plasticity,” Schola- rpedia, Vol. 2, No. 7, 2007, p. 1605. doi:10.4249/scholarpedia.1605 [14] J. J. Gibson, “The Eco-logical Approach to Visual Perception” Houghton Mifflin, Boston, 1979. [15] D. Chang, K. V. Nesbitt and K. Wilkins, “The Gestalt Principle of Continuation Applies to Both the Haptic and Visual Grouping of Elements,” WHC ’07 Proceed-ings of the Second Joint EuroHaptics Conference and Sympo-sium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2007, pp. 15-20. doi:10.1109/WHC.2007.113 [16] R. Eckhorn, H. J. Reitboeck, M. Arndt and P. W. Dicke, “Feature Linking via Synchroniza-tion among Distributed Assemblies: Simulation of Results from Cat Cortex,” Neural Computation, Vol. 2, No. 3, 1990, pp. 293-307. doi:10.1162/neco.1990.2.3.293 [17] Z. W. Shi, Z. Z. Shi, X. Liu and Z. P. Shi, “A Computational Model for Feature Bind-ing,” Science in China, Series C: Life Science, Vol. 51, No. 5, 2009, pp. 470-478. doi:10.1007/s11427-008-0063-3 [18] G. Miller, “How Are Memories Stored and Retrieved?” Science, Vol. 309, No. 5731 2005, p. 92. doi:10.1126/science.309.5731.92 [19] M. J. Dehn, “Working Memory and Academic Learning: Assessment and Interven-tion,” Wiley, New York, 2008. [20] M. Tarsia and E. Sanavio, “Implicit and Explicit Memory Biases in Mixed Anxi-ety-Depression,” Journal of Affective Disorders, Vol. 77, No. 03, 2003, pp. 213-225. doi:10.1016/S0165-0327(02)00119-2 [21] N. Chomsky, “Syntactic Structures,” Mouton, The Hague, 1957. [22] R. Mayeux and E. R. Kandel, “Disorders of Language: The Apha-sias,” In: E. R. Kandel, J. H. Schwarz and T. M. Jessell Eds., Principles of Neural Science, 3rd Edition, Elsevier, Amsterdam, 1991, pp. 840-851. [23] Q. Dong and Z. Z. Shi, “A Research on Introspective Learning Based on CBR,” International Jour-nal of Advanced Intelligence, Vol. 3, No. 1, 2011. pp. 147-157. [24] A. S. Reber, “Implicit Learning and Artificial Grammer,” Journal of Verbal Learning and Verbal Behavior, Vol. 6, No. 6, 1967, pp. 855-863. doi:10.1016/S0022-5371(67)80149-X [25] Z. Z. Shi, “Cogni-tive Science,” Press of USTC, Anhui, 2008. [26] Z. Z. Shi, “Advanced Artificial Intelligence,” Science Press of China, Beijing, 2006. [27] J. Piaget, “Piaget’s Theory,” In: P. Mussen, Ed. Handbook of Child Psychology, 4th Edition, Wiley, New York, 1983. [28] J. Santrock, “A Topical Approach to Life-Span Develop- ment. Chapter 6 Cognitive Development Approaches (200 - 225),” McGraw-Hill, New York, 2004. [29] D. A. Norman, “Emotion and Design: Attractive Things Work Better,” Interactions Magazine, Vol. 4, No. 4, 2002. [30] Ortony, G. L. Clore and A. Collins, “The Cognitive Structure of Emotions,” Cambridge University Press, Cam-bridge, 1988. doi:10.1017/CBO9780511571299 [31] McCarthy, O. L. Mejia, H. T. Liu and A. C. Durham, “Cognitive Appraisal Theory: A Psychoeducational Model for Connecting Thoughts and Feel-ings,” The Annual Convention of the American Psychological Association, San Francisco, 14-18 August 1998. [32] A. Slo-man, “Review of Affective Computing,” AI Magazine, Vol. 20, No. 1, 1999, pp. 127-133. [33] M. Minsky, “The Emotion Machine,” Simon and Schuster, New York City, 2006. [34] J. Velasquez, P. Maes, “Cathexis: A Computational Model of Emotions,” Proceedings of the First International Conference on Autonomous Agents, Marina del Rey, 05 - 08 February 1997. [35] F. Crick, “The Astonishing Hypothesis,” Scribner, Humboldt, 1995. [36] B. J. Baars and S. Franklin, “An Archi-tectural Model of Conscious and Unconscious Brain Functions: Global Workspace Theory and IDA,” Neural Networks, Vol. 20 No. 9, 2007, pp. 955-961. doi:10.1016/j.neunet.2007.09.013 [37] D. Chalmers, “The Conscious Mind: In Search of a Fundamental Theory,” Oxford University Press, Oxford, 1995. [38] Medical dictionary Web-site: http://www.medterms.com/script/main/hp.asp. [39] J. R. Anderson, “The Adaptive Character of Thought,” Erlbaum, Hillsdale, 1993. [40] J. R. Anderson and Y. Qin, “Using Brain Imaging to Extract the Structure of Complex Events at the Ra-tional Time Band,” Journal of Cognitive Neuroscience, Vol. 20, No. 9, 2008, pp. 1624-1636. doi:10.1162/jocn.2008.20108 [41] J. R. Anderson, “Using Neural Imaging to Inform the Instruction of Mathematics,” N. Zhong, K. C. Li, S. F. Lu and L. Chen, Eds., Brain Informatics, International Conference: Lecture Notes in Computer Science, Toronto, 28-30 August 2010. [42] J. R. Anderson, S. A. Betts, J. L. Ferris and J. M. Fincham, “Neural Imaging to Track Men-tal States While Using an Intelligent Tutoring System,” Pro-ceedings of the National Academy of Science, Vol. 107, No. 15, 2010, pp. 7018-7023. doi:10.1073/pnas.1000942107 [43] J. Laird, A. Newell and P. Rosenbloom, “SOAR: An Architecture for General Intelligence,” Artificial Intelli- gence, Vol. 33, No. 1, 1987, pp. 1-64. doi:10.1016/0004-3702(87)90050-6 [44] A. Newell, “Unified Theories of Cognition,” Harvard University Press, Cambridge, 1990. [45] J. Baars and S. Franklin, “How Conscious Experi-ence and Working Memory Interact,” Trends in Cognitive Sci-ence, Vol. 7, No. 4, 2003, pp. 166-172. doi:10.1016/S1364-6613(03)00056-1 [46] D. Friedlander and S. Franklin, “LIDA and a Theory of Mind,” IOS Press, Am-sterdam, pp. 137-148. [47] Z. Z. Shi and X. F. Wang, “A Mind Model CAM in Intelligence Science,” International Journal of Advanced Intelligence, Vol. 3, No. 1, 2011, pp. 119-129. [48] Z. Z. Shi, “Research on Brain-Like Computer,” Com-puter Science, Vol. 5820, 2009, p. 5. doi:10.1007/978-3-642-04875-3_5
[1] J. McCarthy, “The Future of AI-A Manifesto,” AI Magazine, Vol. 26, No. 4, 2005, p. 39. [2] H. Jeff and S. Blakeslee, “On Intelligence, Times Books,” Henry Holt and Company, New York City, 2004. [3] R. Granger, “Engines of the Brain,” AI Magazine, Vol. 27, No. 2, 2006, pp. 15-31. [4] P. Langley, “Cognitive Architectures and General Intelligent Systems,” AI Magazine, Vol. 27, No. 2, 2006, pp. 33-44, [5] K. Sycara, “Multi-Agent Systems,” AI Magazine, Vol. 19, No. 2, 1998, pp. 79-93. [6] N. Cassimatis, “A Cognitive Substrate for Achieving Human-Level Intelligence,” AI Magazine, Vol. 27, No. 2, 2006, pp. 45-56. [7] J. Snaider, R. McCall, S. Franklin, “The LIDA Framework as a General Tool for AGI,” AGI2011. (To be appeared). [8] Intelligence Science Web http://www.intsci.ac.cn/. [9] Z. Z. Shi, “Intelligence Sci-ence,” in Chinese, Tsinghua University Press, Beijing, 2006. [10] Z. Z. Shi, “Artificial Thought and Intelligent Sys-tems,” AI Summer School’94, Beijing, 1994. [11] S. Legg and M. Hutter, “A Collection of Definitions of Intelligence,” 2006. www.vetta.org/shane/intelligence.html. [12] M. F. Bear, B. Connors, M. Paradiso, M. F. Bear, B. W. Connors and M. A. Neuroscience, “Exploring the Brain,” 2nd Edition, Lippincott Williams & Wilkins, Philadelphia 2002. [13] H. Z. Shouval, “Models of Synaptic Plasticity,” Schola- rpedia, Vol. 2, No. 7, 2007, p. 1605. doi:10.4249/scholarpedia.1605 [14] J. J. Gibson, “The Eco-logical Approach to Visual Perception” Houghton Mifflin, Boston, 1979. [15] D. Chang, K. V. Nesbitt and K. Wilkins, “The Gestalt Principle of Continuation Applies to Both the Haptic and Visual Grouping of Elements,” WHC ’07 Proceed-ings of the Second Joint EuroHaptics Conference and Sympo-sium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2007, pp. 15-20. doi:10.1109/WHC.2007.113 [16] R. Eckhorn, H. J. Reitboeck, M. Arndt and P. W. Dicke, “Feature Linking via Synchroniza-tion among Distributed Assemblies: Simulation of Results from Cat Cortex,” Neural Computation, Vol. 2, No. 3, 1990, pp. 293-307. doi:10.1162/neco.1990.2.3.293 [17] Z. W. Shi, Z. Z. Shi, X. Liu and Z. P. Shi, “A Computational Model for Feature Bind-ing,” Science in China, Series C: Life Science, Vol. 51, No. 5, 2009, pp. 470-478. doi:10.1007/s11427-008-0063-3 [18] G. Miller, “How Are Memories Stored and Retrieved?” Science, Vol. 309, No. 5731 2005, p. 92. doi:10.1126/science.309.5731.92 [19] M. J. Dehn, “Working Memory and Academic Learning: Assessment and Interven-tion,” Wiley, New York, 2008. [20] M. Tarsia and E. Sanavio, “Implicit and Explicit Memory Biases in Mixed Anxi-ety-Depression,” Journal of Affective Disorders, Vol. 77, No. 03, 2003, pp. 213-225. doi:10.1016/S0165-0327(02)00119-2 [21] N. Chomsky, “Syntactic Structures,” Mouton, The Hague, 1957. [22] R. Mayeux and E. R. Kandel, “Disorders of Language: The Apha-sias,” In: E. R. Kandel, J. H. Schwarz and T. M. Jessell Eds., Principles of Neural Science, 3rd Edition, Elsevier, Amsterdam, 1991, pp. 840-851. [23] Q. Dong and Z. Z. Shi, “A Research on Introspective Learning Based on CBR,” International Jour-nal of Advanced Intelligence, Vol. 3, No. 1, 2011. pp. 147-157. [24] A. S. Reber, “Implicit Learning and Artificial Grammer,” Journal of Verbal Learning and Verbal Behavior, Vol. 6, No. 6, 1967, pp. 855-863. doi:10.1016/S0022-5371(67)80149-X [25] Z. Z. Shi, “Cogni-tive Science,” Press of USTC, Anhui, 2008. [26] Z. Z. Shi, “Advanced Artificial Intelligence,” Science Press of China, Beijing, 2006. [27] J. Piaget, “Piaget’s Theory,” In: P. Mussen, Ed. Handbook of Child Psychology, 4th Edition, Wiley, New York, 1983. [28] J. Santrock, “A Topical Approach to Life-Span Develop- ment. Chapter 6 Cognitive Development Approaches (200 - 225),” McGraw-Hill, New York, 2004. [29] D. A. Norman, “Emotion and Design: Attractive Things Work Better,” Interactions Magazine, Vol. 4, No. 4, 2002. [30] Ortony, G. L. Clore and A. Collins, “The Cognitive Structure of Emotions,” Cambridge University Press, Cam-bridge, 1988. doi:10.1017/CBO9780511571299 [31] McCarthy, O. L. Mejia, H. T. Liu and A. C. Durham, “Cognitive Appraisal Theory: A Psychoeducational Model for Connecting Thoughts and Feel-ings,” The Annual Convention of the American Psychological Association, San Francisco, 14-18 August 1998. [32] A. Slo-man, “Review of Affective Computing,” AI Magazine, Vol. 20, No. 1, 1999, pp. 127-133. [33] M. Minsky, “The Emotion Machine,” Simon and Schuster, New York City, 2006. [34] J. Velasquez, P. Maes, “Cathexis: A Computational Model of Emotions,” Proceedings of the First International Conference on Autonomous Agents, Marina del Rey, 05 - 08 February 1997. [35] F. Crick, “The Astonishing Hypothesis,” Scribner, Humboldt, 1995. [36] B. J. Baars and S. Franklin, “An Archi-tectural Model of Conscious and Unconscious Brain Functions: Global Workspace Theory and IDA,” Neural Networks, Vol. 20 No. 9, 2007, pp. 955-961. doi:10.1016/j.neunet.2007.09.013 [37] D. Chalmers, “The Conscious Mind: In Search of a Fundamental Theory,” Oxford University Press, Oxford, 1995. [38] Medical dictionary Web-site: http://www.medterms.com/script/main/hp.asp. [39] J. R. Anderson, “The Adaptive Character of Thought,” Erlbaum, Hillsdale, 1993. [40] J. R. Anderson and Y. Qin, “Using Brain Imaging to Extract the Structure of Complex Events at the Ra-tional Time Band,” Journal of Cognitive Neuroscience, Vol. 20, No. 9, 2008, pp. 1624-1636. doi:10.1162/jocn.2008.20108 [41] J. R. Anderson, “Using Neural Imaging to Inform the Instruction of Mathematics,” N. Zhong, K. C. Li, S. F. Lu and L. Chen, Eds., Brain Informatics, International Conference: Lecture Notes in Computer Science, Toronto, 28-30 August 2010. [42] J. R. Anderson, S. A. Betts, J. L. Ferris and J. M. Fincham, “Neural Imaging to Track Men-tal States While Using an Intelligent Tutoring System,” Pro-ceedings of the National Academy of Science, Vol. 107, No. 15, 2010, pp. 7018-7023. doi:10.1073/pnas.1000942107 [43] J. Laird, A. Newell and P. Rosenbloom, “SOAR: An Architecture for General Intelligence,” Artificial Intelli- gence, Vol. 33, No. 1, 1987, pp. 1-64. doi:10.1016/0004-3702(87)90050-6 [44] A. Newell, “Unified Theories of Cognition,” Harvard University Press, Cambridge, 1990. [45] J. Baars and S. Franklin, “How Conscious Experi-ence and Working Memory Interact,” Trends in Cognitive Sci-ence, Vol. 7, No. 4, 2003, pp. 166-172. doi:10.1016/S1364-6613(03)00056-1 [46] D. Friedlander and S. Franklin, “LIDA and a Theory of Mind,” IOS Press, Am-sterdam, pp. 137-148. [47] Z. Z. Shi and X. F. Wang, “A Mind Model CAM in Intelligence Science,” International Journal of Advanced Intelligence, Vol. 3, No. 1, 2011, pp. 119-129. [48] Z. Z. Shi, “Research on Brain-Like Computer,” Com-puter Science, Vol. 5820, 2009, p. 5. doi:10.1007/978-3-642-04875-3_5