Minds and Machines

, Volume 9, Issue 1, pp 57–80 | Cite as

AI as Complex Information Processing

  • Hideyuki Nakashima


In this article, I present a software architecture for intelligent agents. The essence of AI is complex information processing. It is impossible, in principle, to process complex information as a whole. We need some partial processing strategy that is still somehow connected to the whole. We also need flexible processing that can adapt to changes in the environment. One of the candidates for both of these is situated reasoning, which makes use of the fact that an agent is in a situation, so it only processes some of the information – the part that is relevant to that situation. The combination of situated reasoning and context reflection leads to the idea of organic programming, which introduces a new building block of programs called a cell. Cells contain situated programs and the combination of cells is controlled by those programs.

situation theory situated reasoning organic programming dynamic subsumption architecture 


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  1. Barwise, J. (1989), The Situation in Logic. CSLI Lecture Notes, No. 17, Stanford, California.Google Scholar
  2. Barwise, J. and Perry, J. (1983), Situations and Attitudes. Cambridge, MIT Press, MA.Google Scholar
  3. Barwise, J. and Seligman, J. (1997), Information Flow: The Logic of Distributed Systems. Cambridge Univ. Press.Google Scholar
  4. Bertalanffy, L. (1968), General System Theory. New York, George Braziller.Google Scholar
  5. Borota, J., Frank, M., Itoh, A., Nakashima, H., Peters, S., Reilly, M. and Schütze H. (1992), The PROSIT language v1.0. Technical report, CSLI.Google Scholar
  6. Brooks, R.A., (1991), ‘Intelligence Without Representation’; Artificial Intelligence, 47: 139–160.CrossRefGoogle Scholar
  7. Devlin, K., (1991), Logic and Information I: Infons and Situations. Univ. Press, Cambridge. Cooperative architecture project team. Gaea home page., 1996.Google Scholar
  8. Hasida, K. and Matsubara, H., (1990), ‘Partiality of Information and the Structure of the Frame Problem’. In Proc. of Pacific Rim International Conf. on AI 90, pps. 711–716.Google Scholar
  9. Havel, I.M. (1993), ‘Artificial Thought and Emergent Mind’. In Proc. of International Joint Conference on Artificial Intelligence 93, pps 758–766.Google Scholar
  10. Kimura, B. (1994), Kokoro-no Byori-wo Kangaeru (In Japanese. Considerations on Mental Malfunction). Iwanami Shoten, Tokyo.Google Scholar
  11. Kitano, H., Asada, M., Kuniyoshi, Y., Noda, I., Osawa, E., and Matsubara, H. (1997), Robocup-a challenge problem for AI-. AI Magazine, 18(1): 73–85, spring.Google Scholar
  12. LeDoux, J.E., Cicchetti, P., Xagorais, A. and Romanski, L.M. (1990), ‘The Lateral Amygdaloid Nucleus: Sensory Interface of the Amygdala in Fear Conditioning’. The Journal of Neuroscience, 10(4): 1062–1069, April.Google Scholar
  13. Matsumoto, G., Shigematsu, Y. and Ichikawa, M. (1996), ‘The Brain as a Computer’. In Roberto Moreno-Díaz and José Mira-Mira, (eds), Brain Processes, Theories and Models, pps 107–112. Cambridge, MA, MIT Press.Google Scholar
  14. Matsuno, K. (1996), ‘A View from the Inside’. Revue de la Pensee d'Aujour d'Hui, 24(11): 79–92. in Japanese. English version available at Scholar
  15. Maturana, H.R. and Varela, F.J. (1980), Autopoiesis and Cognition: The Realization of the Living. Dordrecht, Holland, D. Reidel Publishing Co.Google Scholar
  16. Minsky, M. (1975), ‘A Framework for Representing Knowledge’. In Patric Winston, editor, The Psychology of Computer Vision. McGraw Hill.Google Scholar
  17. Nakashima, H. (1992), Context reflection. In Proc. of IMSA '92 International Workshop on Reflection and Meta-Level Architecture, pages 172–177.Google Scholar
  18. Nakashima, H. and Noda, I. (1998), ‘Dynamic Subsumption Architecture for Programming Intelligent Agents’. In Proc. of International Conf. on Multi-Agent Systems 98. AAAI Press. 80Google Scholar
  19. Nakashima, H., Noda, I. and Handa, K. (1996), ‘Organic Programming Language Gaea for Multiagents’. In Proc. of International Conf. on Multi-Agent Systems 96, pages 236–243. AAAI Press.Google Scholar
  20. Nakashima, H. and Osawa, I. (1996), ‘Inference with Mental Situations’. In Proc. of the Second Conf. on Information-Theoretic Approaches to Logic, Language, and Computation, pages 153–166.Google Scholar
  21. Nakashima, H., Peters, S. and Schüzte, H. (1991), ‘Communication and Inference through Situations’. In Proc. of IJCAI-91, pages 76–81.Google Scholar
  22. Nakashima, H. and Tutiya, S. (1991), ‘Inference in a Situation about Situations’. In Situation Theory and its Applications, 2, pages 215–227. CSLI Lecture Notes, No. 26, Stanford, California.Google Scholar
  23. Rosenschein, S.J. (1987), ‘Formal Theories of Knowledge in AI and Robotics’. Report 87–84, CSLI, Stanford University, California.Google Scholar
  24. Rössler, O.E. (1987), ‘Endophysics’. In John L. Casti and Anders Karlqvit, editors, Real Brains Artificial Minds. Elsevier Science Publishing Co. Inc.Google Scholar
  25. Russell, S. (1995), ‘Rationality and Intelligence’. In Proc. of IJCAI-95, pages 950–957.Google Scholar
  26. Simon, H. (1995), ‘Explaining the Ineffable: AI on the Topics of Intuition, Insight and Inspiration’. In Proc. of IJCAI-95, pages 939–948.Google Scholar
  27. Stone, P. and Veloso, M. (1998), ‘Task Decomposition and Dynamic Role Assignment for Real-Time Strategic Teamwork’. In Proc. of ATAL '98-Agents, Theories, Architectures, and Languages, pages 369–381.Google Scholar
  28. Tinbergen, N. (1951), The Study of Instinct. Oxford, Clarendon Press.Google Scholar
  29. Ueda, K. (1987), Guarded Horn Clauses. In Eiiti Wada, editor, Logic Programming '85, Lecture Notes in Computer Science 221. Springer-Verlag, 1986. Also in Concurrent Prolog: Collected Papers, Vol. 1, Shapiro E. (ed.), Cambridge, MA. The MIT Press, pp. 140–156.Google Scholar

Copyright information

© Kluwer Academic Publishers 1999

Authors and Affiliations

  • Hideyuki Nakashima
    • 1
  1. 1.ETL (Electrotechnical Laboratories)TsukubaJapan

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