Using Information Theory to Observe Natural Intelligence and Artificial Intelligence

Authors: Lipeng Zhang, Limei Li, Yanming Pearl Zhang

Abstract:

This paper takes a philosophical view as axiom, and reveals the relationship between information theory and Natural Intelligence and Artificial Intelligence under real world conditions. This paper also derives the relationship between natural intelligence and nature. According to communication principle of information theory, Natural Intelligence can be divided into real part and virtual part. Based on information theory principle that Information does not increase, the restriction mechanism of Natural Intelligence creativity is conducted. The restriction mechanism of creativity reveals the limit of natural intelligence and artificial intelligence. The paper provides a new angle to observe natural intelligence and artificial intelligence.

Keywords: Natural intelligence, artificial intelligence, creativity, information theory.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1124555

References:

[1] Shannon, Claude E. (July–October 1948). "A Mathematical Theory of Communication". Bell System Technical Journal 27 (3): 379–423.
[2] Borda, Monica (2011). Fundamentals in Information Theory and Coding. Springer. p. 11. ISBN 978-3-642-20346-6.
[3] Han, Te Sun & Kobayashi, Kingo (2002). Mathematics of Information and Coding. American Mathematical Society. pp. 19–20. ISBN 978-0-8218-4256-0.
[4] Schneider, T.D, Information theory primer with an appendix on logarithms, National Cancer Institute, 14 April 2007.
[5] Carter, Tom (March 2014). An introduction to information theory and entropy (PDF). Santa Fe. Retrieved Aug 2014.Young, “Synthetic structure of industrial plastics (Book style with paper title and editor),” in Plastics, 2nd ed. vol. 3, J. Peters, Ed. New York: McGraw-Hill, 1964, pp. 15–64.
[6] Tian BaoYu edited Zhou JiongPan and Wu WeiLing review Beijing University of Posts and Telecommunications Press
[7] Turing, Alan (October 1950), "Computing Machinery and Intelligence", Mind LIX (236): 433–460, doi:10.1093/mind/LIX.236.433, ISSN 0026-4423, retrieved 2008-08-18.
[8] Poole, David; Mackworth, Alan; Goebel, Randy (1998). Computational Intelligence: A Logical Approach. New York: Oxford University Press. ISBN 0-19-510270-3.
[9] Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBN 0-13-790395-2.
[10] McCarthy, John; Minsky, Marvin; Rochester, Nathan; Shannon, Claude (1955). "A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence Artificial Intelligence". Archived from the original on 26 August 2007. Retrieved 30 August 2007\
[11] Loehlin, J. C.; Perloff, R.; Sternberg, R. J.; Urbina, S. (1996). "Intelligence: Knowns and unknowns". American Psychologist 51 (2): 77. doi:10.1037/0003-
[12] Maich, Aloysius (1995). "A Hobbes Dictionary". Blackwell. p. 305
[13] Nidditch, Peter. "Foreword". An Essay Concerning Human Understanding. Oxford University Press. p. xxii
[14] Gottfredson, Linda S. (1997). "Mainstream Science on Intelligence. Intelligence 24: 13–23. doi:10.1016/s0160-2896(97)90011-8. ISSN 0160-2896.
[15] Neisser, Ulrich; Boodoo, Gwyneth; Bouchard, Thomas J.; Boykin, A. Wade; Brody, Nathan; Ceci, Stephen J.; Halpern, Diane F.; Loehlin, John C.; Perloff, Robert; Sternberg, Robert J.; Urbina, Susana (1996). "Intelligence: Knowns and unknowns". American Psychologist 51: 77–101. ISSN 0003-066X. Retrieved9 October 2014.
[16] Legg, Shane and Hutter, Marcus (2006) A Formal Measure of Machine Intelligence. Technical Report. UNSPECIFIED. Proceedings of the 16th Annual Machine Learning Conference of Belgium and The Netherlands, Belelearn (2006)