Skip to main content
Springer Nature Link
Log in

Two Paradigms Are Better Than One, and Multiple Paradigms Are Even Better

  • Conference paper
Conceptual Structures: Leveraging Semantic Technologies (ICCS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5662))

Included in the following conference series:

  • 697 Accesses

Abstract

During the past half century, the field of artificial intelligence has developed a large number of theories, paradigms, technologies, and tools. Many AI systems are based on one dominant paradigm with a few subsidiary modules for handling exceptions or special cases. Some systems are built from components that perform different tasks, but each component is based on a single paradigm. Since people freely switch from one method of thinking or reasoning to another, some cognitive scientists believe that the ability to integrate multiple methods of reasoning is key to human-like flexibility. In his book The Society of Mind, Minsky (1986) presented an architecture for intelligence based on a society of heterogeneous agents that use different reasoning methods to solve different problems or different aspects of the same problem. That idea is intriguing, but it raises many serious issues:  how to coordinate multiple agents, distribute tasks among them, evaluate their results, encourage agents that consistently produce good results, inhibit agents that produce misleading, irrelevant, or unfruitful results, and integrate all the results into a coherent response. The most difficult problem is to enable multiple heterogeneous agents, acting independently, to produce the effect of a single mind with a unified personality that can pursue and accomplish coherent goals. This article discusses ways of organizing a society of heterogeneous agents as an integrated system with flexible methods of reasoning, learning, and language processing.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Baum, E.B.: What is Thought? MIT Press, Cambridge (2004)

    Google Scholar 

  2. Bröker, N.: Eine Dependenzgrammatik zur Kopplung heterogener Wissensquellen. Max Niemeyer Verlag, Tübingen (1999)

    Google Scholar 

  3. Brooks, R.A.: Intelligence without representation. Artificial Intelligence 47, 139–159 (1991)

    Article  Google Scholar 

  4. Eberbach, E., Goldin, D., Wegner, P.: Turing’s ideas and models of computation. In: Teuscher, C. (ed.) Alan Turing: Life and Legacy of a Great Thinker. Springer, Berlin (2004)

    Google Scholar 

  5. Falkenhainer, B., Forbus, K.D., Gentner, D.: The structure mapping engine: algorithm and examples. Artificial Intelligence 41, 1–63 (1989)

    Article  MATH  Google Scholar 

  6. Gelernter, D.: Generative communication in Linda. ACM Transactions on Programming Languages and Systems, 80–112 (1985)

    Google Scholar 

  7. Hahn, U., Schacht, S., Bröker, N.: Concurrent natural language parsing: The ParseTalk model. International Journal of Human-Computer Studies 41, 179–222 (1994)

    Article  Google Scholar 

  8. Hahn, U., Bröker, N., Neuhaus, P.: Let’s ParseTalk: Message-passing protocols for object-oriented parsing. In: Bunt, H., Nijholt, A. (eds.) Recent Advances in Parsing Technology. Kluwer, Dordrecht (2000)

    Google Scholar 

  9. ISO/IEC 2007 Common Logic (CL) — A Framework for a family of Logic-Based Languages, IS 24707, International Organisation for Standardisation (2007)

    Google Scholar 

  10. Lenat, D.B.: Cyc: A large-scale investment in knowledge infrastructure. Communications of the ACM 38(11), 33–38 (1995)

    Article  Google Scholar 

  11. Levinson, R.A., Ellis, G.: Multilevel hierarchical retrieval. Knowledge Based Systems 5(3), 233–244 (1992)

    Article  Google Scholar 

  12. Majumdar, A.K., Sowa, J.F., Stewart, J.: Pursuing the goal of language understanding. In: Eklund, P., Haemmerlé, O. (eds.) ICCS 2008. LNCS (LNAI), vol. 5113, pp. 21–42. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  13. Majumdar, A., Keeler, M., Tarau, P., Sowa, J.: Semantic distances as knowledge capture constraints. In: First Workshop on Knowledge Capture and Constraint Programming (KCCP 2007), Whistler, BC (2007)

    Google Scholar 

  14. McCarthy, J.: Elephant 2000: A programming language based on speech acts (1989), http://www-formal.stanford.edu/jmc/elephant.html

  15. Milner, R.: Communicating and Mobile Systems: The Π calculus. Cambridge University Press, Cambridge (1999)

    MATH  Google Scholar 

  16. Minsky, M.: K-lines: A Theory of Memory. Cognitive Science 4, 117–133 (1980)

    Article  Google Scholar 

  17. Minsky, M.: The Society of Mind. Simon and Schuster, New York (1986)

    Google Scholar 

  18. Minsky, M.: Logical vs. analogical or symbolic vs. connectionist or neat vs. scruffy. AI Magazine 12(2), 34–51 (1991)

    Google Scholar 

  19. Minsky, M.: Review of Allen Newell’s Unified Theories of Cognition. Artificial Intelligence 59, 343–354 (1993)

    Article  Google Scholar 

  20. Minsky, M.: The Emotion Machine: Commonsense Thinking. In: Artificial Intelligence, and the Future of the Human Mind. Simon & Schuster, New York (2006)

    Google Scholar 

  21. Monderer, D., Tennenholtz, M., Varian, H.: Economics and artificial intelligence. Games and Economic Behavior 35(1-2), 1–5 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  22. Newell, A.: Unified Theories of Cognition. Harvard University Press, Cambridge (1990)

    Google Scholar 

  23. Peirce, C.S.: Logic, Considered as Semeiotic, MS L75, edited by Ransdell, J. (1902), http://members.door.net/arisbe/menu/library/bycsp/l75/l75.htm

  24. Rhodes, J., Boyer, S., Kreulen, J., Chen, Y., Ordonez, P.: Mining patents using molecular similarity search. In: Pacific Symposium on Biocomputing, vol. 12, pp. 304–315 (2007)

    Google Scholar 

  25. Sarraf, Q., Ellis, G.: Business rules in retail: The Tesco.com story. Business Rules Journal 7(6) (2006), http://www.brcommunity.com/a2006/n014.html

  26. Selfridge, O.G.: Pandemonium: A paradigm for learning. In: The Mechanization of Thought Processes, NPL Symposium No. 10, Her Majesty’s Stationery Office, London, pp. 511–526 (1959)

    Google Scholar 

  27. Singh, P.: Examining the society of mind. Computing and Artificial Intelligence 22(6) (2003)

    Google Scholar 

  28. Sleator, D., Temperley, D.: Parsing English with a link grammar. In: Third International Workshop on Parsing Technologies (1993), http://www.cs.cmu.edu/afs/cs.cmu.edu/project/link/pub/www/papers/ps/LG-IWPT93.pdf

  29. Sowa, J.F.: Conceptual Structures: Information Processing in Mind and Machine. Addison-Wesley, Reading (1984)

    MATH  Google Scholar 

  30. Sowa, J.F.: Architectures for intelligent systems. IBM Systems Journal 41(3), 331–349 (2002), http://researchweb.watson.ibm.com/journal/sj41-3.html

    Article  MathSciNet  Google Scholar 

  31. Sowa, J.F.: Graphics and languages for the Flexible Modular Framework. In: Wolff, K.E., Pfeiffer, H.D., Delugach, H.S. (eds.) ICCS 2004. LNCS (LNAI), vol. 3127, pp. 31–51. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  32. Sowa, J.F.: Conceptual graphs. In: van Harmelen, et al. (eds.), pp. 213–237 (2008)

    Google Scholar 

  33. Sowa, J.F., Majumdar, A.K.: Analogical reasoning. In: Ganter, B., de Moor, A., Lex, W. (eds.) ICCS 2003. LNCS (LNAI), vol. 2746, pp. 16–36. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  34. Turing, A.M.: Systems of logic based on ordinals. Proc. London Mathematical Society, Series 2 45, 161–228 (1939)

    Article  MATH  Google Scholar 

  35. van der Hoek, W., Wooldridge, M.: Multiagent systems. In: van Harmelen, et al. (eds.), pp. 887–928 (2008)

    Google Scholar 

  36. van Harmelen, F., Lifschitz, V., Porter, B. (eds.): Handbook of Knowledge Representation. Elsevier, Amsterdam (2008)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. VivoMind Intelligence, Inc., Germany

    Arun K. Majumdar & John F. Sowa

Authors
  1. Arun K. Majumdar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John F. Sowa
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institut AIFB, Universität Karlsruhe (TH), 76128, Karlsruhe, Germany

    Sebastian Rudolph

  2. SAP Research Center CEC Dresden, Chemnitzer Strasse 48, 01187, Dresden, Germany

    Frithjof Dau

  3. Higher School of Economics, Department of Applied Mathematics and Information Science, State University, Kirpichnaya 33/5, 105679, Moscow, Russia

    Sergei O. Kuznetsov

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Majumdar, A.K., Sowa, J.F. (2009). Two Paradigms Are Better Than One, and Multiple Paradigms Are Even Better. In: Rudolph, S., Dau, F., Kuznetsov, S.O. (eds) Conceptual Structures: Leveraging Semantic Technologies. ICCS 2009. Lecture Notes in Computer Science(), vol 5662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03079-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03079-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03078-9

  • Online ISBN: 978-3-642-03079-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics