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On Defining Artificial Intelligence

   | Aug 19, 2019

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Adams, E. W. 1998. A Primer of Probability Logic. Stanford, California: CSLI Publications.Search in Google Scholar

Albus, J. S. 1991. Outline for a Theory of Intelligence. IEEE Transactions on Systems, Man, and Cybernetics 21(3):473–509.10.1109/21.97471Search in Google Scholar

Allen, J. F. 1998. AI growing up: the changes and opportunities. AI Magazine 19(4):13–23.Search in Google Scholar

Aristotle. 1882. The Organon, or, Logical treatises of Aristotle. London: George Bell. Translated by O. F. Owen.Search in Google Scholar

Bach, J. 2009. Principles of Synthetic Intelligence PSI: An Architecture of Motivated Cognition. Oxford: Oxford University Press.10.1093/acprof:oso/9780195370676.001.0001Search in Google Scholar

Beattie, C.; Leibo, J. Z.; Teplyashin, D.; Ward, T.; Wainwright, M.; Küttler, H.; Lefrancq, A.; Green, S.; Valdés, V.; Sadik, A.; Schrittwieser, J.; Anderson, K.; York, S.; Cant, M.; Cain, A.; Bolton, A.; Gaffney, S.; King, H.; Hassabis, D.; Legg, S.; and Petersen, S. 2016. DeepMind Lab. CoRR abs/1612.03801.Search in Google Scholar

Bhatnagar, S.; Alexandrova, A.; Avin, S.; Cave, S.; Cheke, L.; Crosby, M.; Feyereisl, J.; Halina, M.; Loe, B. S.; hÉigeartaigh, S. O.; Martnez-Plumed, F.; Price, H.; Shevlin, H.; Weller, A.; Winfield, A.; and Hernández-Orallo, J. 2018. Mapping Intelligence: Requirements and Possibilities. In Müller, V. C., ed., Philosophy and Theory of Artificial Intelligence 2017. Berlin: Springer. 117–135.10.1007/978-3-319-96448-5_13Search in Google Scholar

Birnbaum, L. 1991. Rigor mortis: a response to Nilsson’s “Logic and artificial intelligence”. Artificial Intelligence 47:57–77.10.1016/0004-3702(91)90050-TSearch in Google Scholar

Bostrom, N. 2014. Superintelligence: Paths, Dangers, Strategies. Oxford, UK: Oxford University Press, 1st edition.Search in Google Scholar

Brachman, R. J. 2006. (AA)AI — more than the sum of its parts, 2005 AAAI Presidential Address. AI Magazine 27(4):19–34.Search in Google Scholar

Cabrol, N. A. 2016. Alien Mindscapes – A Perspective on the Search for Extraterrestrial Intelligence. Astrobiology 16:661–676.10.1089/ast.2016.1536Search in Google Scholar

Carnap, R. 1950. Logical Foundations of Probability. Chicago: The University of Chicago Press.Search in Google Scholar

Cohen, P. R. 2005. If Not Turing’s Test, then what? AI Magazine 26:61–67.Search in Google Scholar

Davis, R. 1998. What are intelligence? and why? 1996 AAAI Presidential Address. AI Magazine 19(1):91–111.Search in Google Scholar

Domingos, P. 2018. The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. New York, NY, USA: Basic Books, Inc.Search in Google Scholar

Executive Office of the President, USA. 2016. The National Artificial Intelligence Research and Development Strategic Plan.Search in Google Scholar

Feigenbaum, E. A., and Feldman, J., eds. 1963. Computers and Thought. New York: McGraw-Hill.Search in Google Scholar

Feigenbaum, E. A., and McCorduck, P. 1983. The Fifth Generation: Artificial Intelligence and Japan’s Computer Challenge to the world. Reading, Massachusetts: Addison-Wesley Publishing Company.Search in Google Scholar

Flach, P. 2012. Machine Learning: The Art and Science of Algorithms That Make Sense of Data. New York, NY, USA: Cambridge University Press.10.1017/CBO9780511973000Search in Google Scholar

Franklin, S. 2007. A foundational architecture for artificial general intelligence. In Goertzel, B., and Wang, P., eds., Advance of Artificial General Intelligence. Amsterdam: IOS Press. 36–54.Search in Google Scholar

Freeman, W. J. 1999. Consciousness, intentionality and causality. Journal of Consciousness Studies 6(11-12):143–172.Search in Google Scholar

Goertzel, B., and Pennachin, C., eds. 2007. Artificial General Intelligence. New York: Springer.10.1007/978-3-540-68677-4Search in Google Scholar

Goertzel, B. 2009. Cognitive Synergy: A Universal Principle for Feasible General Intelligence? Dynamical Psychology.10.1109/COGINF.2009.5250694Search in Google Scholar

Goertzel, B. 2014. Artificial General Intelligence: Concept, State of the Art, and Future Prospects. Journal of Artificial General Intelligence 5(1):1–46.10.2478/jagi-2014-0001Search in Google Scholar

Goldman Sachs. 2016. Profiles in Innovation: Artificial Intelligence - AI, Machine Learning and Data Fuel the Future of Productivity.Search in Google Scholar

Goldstein, S.; Princiotta, D.; and Naglieri, J. 2015. Handbook of intelligence: Evolutionary theory, historical perspective, and current concepts. New York: Springer.10.1007/978-1-4939-1562-0Search in Google Scholar

Gottfredson, L. S. 1997. Mainstream science on intelligence: an editorial with 52 signatories, history, and bibliography. Intelligence 24:13–23.10.1016/S0160-2896(97)90011-8Search in Google Scholar

Hájek, A. 2012. Interpretations of Probability. In Zalta, E. N., ed., The Stanford Encyclopedia of Philosophy. Winter 2012 edition. URL: http://plato.stanford.edu/archives/win2012/entries/probability-interpret/, accessed in May 20, 2019.Search in Google Scholar

Hawkins, J., and Blakeslee, S. 2004. On Intelligence. New York: Times Books.Search in Google Scholar

Hayes, P., and Ford, K. 1995. Turing Test Considered Harmful. In Mellish, C. S., ed., Proceedings of the 14th International Joint Conference on Artificial Intelligence - Volume 1, 972–977.Search in Google Scholar

Hayes, P. J. 1977. In Defense of Logic. In Reddy, R., ed., Proceedings of the 5th International Joint Conference on Artificial Intelligence, 559–565.Search in Google Scholar

Hearst, M. A., and Hirsh, H. 2000. AI’s Greatest Trends and Controversies. IEEE Intelligent Systems 8–17.10.1109/5254.820322Search in Google Scholar

Hernández-Orallo, J. 2017. The Measure of All Minds: Evaluating Natural and Artificial Intelligence. Cambridge: Cambridge University Press.10.1017/9781316594179Search in Google Scholar

Hofstadter, D. R., and FARG. 1995. Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought. New York: Basic Books.Search in Google Scholar

Hofstadter, D. R. 1979. Gödel, Escher, Bach: an Eternal Golden Braid. New York: Basic Books.Search in Google Scholar

Hofstadter, D. R. 1985. Waking up from the Boolean dream, or, subcognition as computation. In Metamagical Themas: Questing for the Essence of Mind and Pattern. New York: Basic Books. chapter 26.Search in Google Scholar

Holland, J. H. 1992. Adaptation in Natural and Artificial Systems: An Introductory Analysis With Applications to Biology, Control, and Artificial Intelligence. Cambridge, Massachusetts: MIT Press.10.7551/mitpress/1090.001.0001Search in Google Scholar

Hopcroft, J. E.; Motwani, R.; and Ullman, J. D. 2007. Introduction to Automata Theory, Languages, and Computation. Boston: Addison-Wesley, 3rd edition.Search in Google Scholar

Hsu, F.-h.; Campbell, M. S.; and Hoane, Jr., A. J. 1995. Deep Blue System Overview. In Proceedings of the 9th International Conference on Supercomputing, 240–244. New York, NY, USA: ACM.10.1145/224538.224567Search in Google Scholar

Hume, D. 1748. An Enquiry Concerning Human Understanding. London.10.1093/oseo/instance.00032980Search in Google Scholar

Hutter, M. 2005. Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability. Berlin: Springer.Search in Google Scholar

Kirsh, D. 1991. Foundations of AI: the big issues. Artificial Intelligence 47:3–30.10.1016/0004-3702(91)90048-OSearch in Google Scholar

Koene, R., and Deca, D. 2013. Editorial: Whole Brain Emulation seeks to Implement a Mind and its General Intelligence through System Identification. Journal of Artificial General Intelligence 4:1–9.10.2478/jagi-2013-0012Search in Google Scholar

Kowalski, R. 1979. Logic for Problem Solving. New York: North Holland.Search in Google Scholar

Kuhn, T. S. 1970. The Structure of Scientific Revolutions. Chicago University Press, 2nd edition.Search in Google Scholar

Kurzweil, R. 2006. The Singularity Is Near: When Humans Transcend Biology. New York: Penguin Books.Search in Google Scholar

Laird, J. E.; Wray, R. E.; Marinier, R. P.; and Langley, P. 2009. Claims and challenges in evaluating human-level intelligent systems. In Goertzel, B.; Hitzler, P.; and Hutter, M., eds., Proceedings of the Second Conference on Artificial General Intelligence, 91–96.Search in Google Scholar

Laird, J. E. 2012. The Soar Cognitive Architecture. Cambridge, Massachusetts: MIT Press.10.7551/mitpress/7688.001.0001Search in Google Scholar

Lake, B. M.; Ullman, T. D.; Tenenbaum, J. B.; and Gershman, S. J. 2017. Building machines that learn and think like people. Behavioral and Brain Sciences 40:E253.10.1017/S0140525X1600183727881212Search in Google Scholar

LeCun, Y.; Bengio, Y.; and Hinton, G. 2015. Deep Learning. Nature 521:436–444.10.1038/nature1453926017442Search in Google Scholar

Legg, S., and Hutter, M. 2007. Universal intelligence: a definition of machine intelligence. Minds & Machines 17(4):391–444.10.1007/s11023-007-9079-xSearch in Google Scholar

Leimeister, J. M. 2010. Collective Intelligence. Business & Information Systems Engineering 2(4):245–248.10.1007/s12599-010-0114-8Search in Google Scholar

Luger, G. F. 2008. Artificial Intelligence: Structures and Strategies for Complex Problem Solving. Boston: Pearson, 6th edition.Search in Google Scholar

Marcus, G.; Rossi, F.; and Veloso, M. M. 2016. Beyond the Turing Test. AI Magazine 37(1):3–4.10.1609/aimag.v37i1.2650Search in Google Scholar

Markram, H. 2006. The Blue Brain Project. Nature Reviews Neuroscience 7(2):153–160.10.1038/nrn1848Search in Google Scholar

Marr, D. 1977. Artificial intelligence: a personal view. Artificial Intelligence 9:37–48.10.1016/0004-3702(77)90013-3Search in Google Scholar

Marr, D. 1982. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. San Francisco: W. H. Freeman & Co.Search in Google Scholar

McCarthy, J.; Minsky, M.; Rochester, N.; and Shannon, C. 1955. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. URL: http://www-formal.stanford.edu/jmc/history/dartmouth.html, accessed in May 20, 2019.Search in Google Scholar

McCarthy, J. 1988. Mathematical logic in artificial intelligence. Dædalus 117(1):297–311.Search in Google Scholar

McCarthy, J. 2007. From here to human-level AI. Artificial Intelligence 171:1174–1182.10.1016/j.artint.2007.10.009Search in Google Scholar

McCorduck, P. 2004. Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence. Natick, MA: A. K. Peters, Ltd., 2nd edition.Search in Google Scholar

McCulloch, W. S., and Pitts, W. H. 1943. A logical calculus of ideas immanent in neural activity. Bulletin of Mathematical Biophysics 5:115–133.10.1007/BF02478259Search in Google Scholar

McDermott, D. 1987. A critique of pure reason. Computational Intelligence 3:151–160.10.1111/j.1467-8640.1987.tb00183.xSearch in Google Scholar

McDermott, D. 2007. Level-headed. Artificial Intelligence 171:1183–1186.10.1016/j.artint.2007.10.013Search in Google Scholar

Medin, D. L., and Ross, B. H. 1992. Cognitive Psychology. Fort Worth: Harcourt Brace Jovanovich.Search in Google Scholar

Michalski, R.; Carbonell, J.; and Mitchell, T., eds. 1984. Machine Learning: An Artificial Intelligence Approach. Springer-Verlag.Search in Google Scholar

Minsky, M.; Singh, P.; and Sloman, A. 2004. The St. Thomas common sense symposium: designing architectures for human-level intelligence. AI Magazine 25(2):113–124.Search in Google Scholar

Minsky, M. 1983. Introduction to the COMTEX Microfiche Edition of the Early MIT Artificial Intelligence Memos. AI Magazine 4(1):19–22.Search in Google Scholar

Minsky, M. 1985a. The Society of Mind. New York: Simon and Schuster.Search in Google Scholar

Minsky, M. 1985b. Why intelligent aliens will be intelligible. In Regis, E., ed., Extraterrestrials: Science and Alien Intelligence. Cambridge: Cambridge University Press. 117–128.Search in Google Scholar

Minsky, M. 1990. Logical vs. analogical or symbolic vs. connectionist or neat vs. scruffy. In Winston, P. H., and Shellard, S. A., eds., Artificial Intelligence at MIT, Vol. 1: Expanding Frontiers. Cambridge, Massachusetts: MIT Press. 218–243.Search in Google Scholar

Minsky, M. 2006. The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind. Simon & Schuster.Search in Google Scholar

Monett, D., and Lewis, C. W. P. 2018. Getting clarity by defining Artificial Intelligence - A Survey. In Müller, V. C., ed., Philosophy and Theory of Artificial Intelligence 2017. Berlin: Springer. 212–214.10.1007/978-3-319-96448-5_21Search in Google Scholar

Newell, A., and Simon, H. A. 1963. GPS, a program that simulates human thought. In Feigenbaum, E. A., and Feldman, J., eds., Computers and Thought. McGraw-Hill, New York. 279–293.Search in Google Scholar

Newell, A., and Simon, H. A. 1976. Computer science as empirical inquiry: symbols and search. Communications of the ACM 19(3):113–126.10.1145/360018.360022Search in Google Scholar

Newell, A. 1990. Unified Theories of Cognition. Cambridge, Massachusetts: Harvard University Press.Search in Google Scholar

Nilsson, N. J. 1986. Probabilistic logic. Artificial Intelligence 28:71–87.10.1016/0004-3702(86)90031-7Search in Google Scholar

Nilsson, N. J. 1991. Logic and artificial intelligence. Artificial Intelligence 47:31–56.10.1016/0004-3702(91)90049-PSearch in Google Scholar

Nilsson, N. J. 1998. Artificial Intelligence: A New Synthesis. San Francisco: Morgan Kaufmann.Search in Google Scholar

Nilsson, N. J. 2005. Human-level artificial intelligence? Be serious! AI Magazine 26(4):68–75.Search in Google Scholar

Nilsson, N. J. 2009. The Quest for Artificial Intelligence: A History of Ideas and Achievements. Cambridge: Cambridge University Press.10.1017/CBO9780511819346Search in Google Scholar

Peirce, C. S. 1931. Collected Papers of Charles Sanders Peirce, volume 2. Cambridge, Massachusetts: Harvard University Press.Search in Google Scholar

Piaget, J. 1960. The Psychology of Intelligence. Paterson, New Jersey: Littlefield, Adams & Co.Search in Google Scholar

Piaget, J. 1963. The Origins of Intelligence in Children. New York: W.W. Norton & Company, Inc. Translated by M. Cook.Search in Google Scholar

Poole, D. L., and Mackworth, A. K. 2017. Artificial Intelligence: Foundations of Computational Agents. Cambridge: Cambridge University Press, 2 edition.10.1017/9781108164085Search in Google Scholar

Reeke, G. N., and Edelman, G. M. 1988. Real brains and artificial intelligence. Dædalus 117(1):143–173.Search in Google Scholar

Regis, E., ed. 1985. Extraterrestrials: Science and alien intelligence.Search in Google Scholar

Roland, A., and Shiman, P. 2002. Strategic computing : DARPA and the quest for machine intelligence, 1983-1993. Cambridge, Massachusetts: MIT Press.Search in Google Scholar

Rumelhart, D. E., and McClelland, J. L. 1986. PDP models and general issues in cognitive science. In Rumelhart, D. E., and McClelland, J. L., eds., Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol. 1, Foundations. Cambridge, Massachusetts: MIT Press. 110–146.Search in Google Scholar

Russell, S., and Norvig, P. 2002. Artificial Intelligence: A Modern Approach. Upper Saddle River, New Jersey: Prentice Hall, 2nd edition.Search in Google Scholar

Russell, S., and Norvig, P. 2010. Artificial Intelligence: A Modern Approach. Upper Saddle River, New Jersey: Prentice Hall, 3rd edition.Search in Google Scholar

Russell, S., and Wefald, E. H. 1991. Do the Right Thing: Studies in Limited Rationality. Cambridge, Massachusetts: MIT Press.Search in Google Scholar

Russell, S. 1997. Rationality and intelligence. Artificial Intelligence 94:57–77.10.1016/S0004-3702(97)00026-XSearch in Google Scholar

Schank, R. C. 1991. Where is the AI? AI Magazine 12(4):38–49.10.3233/AIC-1991-4110Search in Google Scholar

Searle, J. 1980. Minds, brains, and programs. The Behavioral and Brain Sciences 3:417–424.10.1017/S0140525X00005756Search in Google Scholar

Shannon, C. E., and Weaver, W. 1949. The mathematical theory of communication. Urbana, IL: The University of Illinois Press.Search in Google Scholar

Shapiro, S. C. 1992. Artificial Intelligence. In Shapiro, S. C., ed., Encyclopedia of Artificial Intelligence. New York: John Wiley, 2 edition. 54–57.Search in Google Scholar

Silver, D.; Huang, A.; Maddison, C. J.; Guez, A.; Sifre, L.; van den Driessche, G.; Schrittwieser, J.; Antonoglou, I.; Panneershelvam, V.; Lanctot, M.; Dieleman, S.; Grewe, D.; Nham, J.; Kalchbrenner, N.; Sutskever, I.; Lillicrap, T.; Leach, M.; Kavukcuoglu, K.; Graepel, T.; and Hassabis, D. 2016. Mastering the game of Go with deep neural networks and tree search. Nature 529:484–489.10.1038/nature1696126819042Search in Google Scholar

Simon, H. A.; Langley, P. W.; and Bradshaw, G. L. 1981. Scientific Discovery as Problem Solving. Synthese 47:1–27.10.1007/BF01064262Search in Google Scholar

Simon, H. A. 1957. Models of Man: Social and Rational. New York: John Wiley.10.2307/2550441Search in Google Scholar

Simon, H. A. 1983. Reason in Human Affairs. Stanford, California: Stanford University Press.Search in Google Scholar

Solomonoff, R. J. 1964. A formal theory of inductive inference. Part I and II. Information and Control 7(1-2):1–22,224–254.Search in Google Scholar

Thórisson, K. R.; Bieger, J.; Li, X.; and Wang, P. 2019. Cumulative Learning. In Proceedings of the Twelfth Conference on Artificial General Intelligence. To appear.10.1007/978-3-030-27005-6_20Search in Google Scholar

Thórisson, K. R. 2012. A New Constructivist AI: From Manual Methods to Self-Constructive Systems. In Wang, P., and Goertzel, B., eds., Theoretical Foundations of Artificial General Intelligence. Paris: Atlantis Press. 145–171.10.2991/978-94-91216-62-6_9Search in Google Scholar

Thórisson, K. R. 2013. Reductio ad Absurdum: On Oversimplification in Computer Science and its Pernicious Effect on Artificial Intelligence Research. AGI-13 workshop on Formalizing Mechanisms for Artificial General Intelligence and Cognition, Beijing, China, July 31st. Retrieved from http://alumni.media.mit.edu/~kris/ftp/Thorisson-ReductioAdAbsurdum-AGI2013.pdf in May 20, 2019.Search in Google Scholar

Tomasello, M. 2000. Primate Cognition: Introduction to the Issue. Cognitive Science 24(3):351–361.10.1207/s15516709cog2403_1Search in Google Scholar

Turing, A. M. 1950. Computing machinery and intelligence. Mind LIX:433–460.10.1093/mind/LIX.236.433Search in Google Scholar

Tversky, A., and Kahneman, D. 1974. Judgment under uncertainty: heuristics and biases. Science 185:1124–1131.10.1126/science.185.4157.1124Search in Google Scholar

von Neumann, J. 1958. The Computer and the Brain. New Haven, CT: Yale University Press.Search in Google Scholar

Wang, P., and Goertzel, B. 2007. Introduction: Aspects of artificial general intelligence. In Goertzel, B., and Wang, P., eds., Advance of Artificial General Intelligence. Amsterdam: IOS Press. 1–16.Search in Google Scholar

Wang, P., and Hammer, P. 2015. Issues in Temporal and Causal Inference. In Bieger, J.; Goertzel, B.; and Potapov, A., eds., Proceedings of the Eighth Conference on Artificial General Intelligence, 208–217.Search in Google Scholar

Wang, P., and Li, X. 2016. Different Conceptions of Learning: Function Approximation vs. Self-Organization. In Steunebrink, B.; Wang, P.; and Goertzel, B., eds., Proceedings of the Ninth Conference on Artificial General Intelligence, 140–149.Search in Google Scholar

Wang, P.; Liu, K.; and Dougherty, Q. 2018. Conceptions of Artificial Intelligence and Singularity. Information 9(4).10.3390/info9040079Search in Google Scholar

Wang, P. 1994. On the Working Definition of Intelligence. Technical Report 94, Center for Research on Concepts and Cognition, Indiana University, Bloomington, Indiana.Search in Google Scholar

Wang, P. 1995. Non-Axiomatic Reasoning System: Exploring the Essence of Intelligence. Ph.D. Dissertation, Indiana University.Search in Google Scholar

Wang, P. 1996. Heuristics and normative models of judgment under uncertainty. International Journal of Approximate Reasoning 14(4):221–235.10.1016/0888-613X(95)00091-TSearch in Google Scholar

Wang, P. 2001. Wason’s cards: what is wrong. In Chen, L., and Zhuo, Y., eds., Proceedings of the Third International Conference on Cognitive Science, 371–375.Search in Google Scholar

Wang, P. 2004a. The limitation of Bayesianism. Artificial Intelligence 158(1):97–106.10.1016/j.artint.2003.09.003Search in Google Scholar

Wang, P. 2004b. Problem solving with insufficient resources. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems 12(5):673–700.Search in Google Scholar

Wang, P. 2004c. Toward a unified artificial intelligence. In Papers from the 2004 AAAI Fall Symposium on Achieving Human-Level Intelligence through Integrated Research and Systems, 83–90.Search in Google Scholar

Wang, P. 2005. Experience-grounded semantics: a theory for intelligent systems. Cognitive Systems Research 6(4):282–302.10.1016/j.cogsys.2004.08.003Search in Google Scholar

Wang, P. 2006a. Artificial Intelligence: What it is, and what it should be. In Lebiere, C., and Wray, R., eds., Papers from the AAAI Spring Symposium on Between a Rock and a Hard Place: Cognitive Science Principles Meet AI-Hard Problems, 97–102.Search in Google Scholar

Wang, P. 2006b. Rigid Flexibility: The Logic of Intelligence. Dordrecht: Springer.Search in Google Scholar

Wang, P. 2008. What do you mean by “AI”. In Wang, P.; Goertzel, B.; and Franklin, S., eds., Proceedings of the First Conference on Artificial General Intelligence, 362–373.Search in Google Scholar

Wang, P. 2009. Case-by-case problem solving. In Goertzel, B.; Hitzler, P.; and Hutter, M., eds., Proceedings of the Second Conference on Artificial General Intelligence, 180–185.Search in Google Scholar

Wang, P. 2011. The Assumptions on Knowledge and Resources in Models of Rationality. International Journal of Machine Consciousness 3(1):193–218.10.1142/S1793843011000686Search in Google Scholar

Wang, P. 2012. Theories of Artificial Intelligence – Meta-theoretical considerations. In Wang, P., and Goertzel, B., eds., Theoretical Foundations of Artificial General Intelligence. Paris: Atlantis Press. 305–323.10.2991/978-94-91216-62-6_16Search in Google Scholar

Wang, P. 2013. Non-Axiomatic Logic: A Model of Intelligent Reasoning. Singapore: World Scientific.10.1142/8665Search in Google Scholar

Wason, P. C., and Johnson-Laird, P. N. 1972. Psychology of Reasoning: Structure and Content. Cambridge, Massachusetts: Harvard University Press.Search in Google Scholar

Wiener, N. 1948. Cybernetics, or control and communication in the animal and the machine. New York: John Wiley & Sons, Inc.Search in Google Scholar

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