Edison: An Engineering Design Invention System Operating Naively

  • Michael G. Dyer
  • Margot Flowers
  • Jack Hodges
Conference paper


The goal of the EDISON project is to design a program capable of creating novel mechani-cal devices, by using knowledge of naive physical relationships, qualitative reasoning, plan-ning, and discovery/invention heuristics applied to abstract devices organized and indexed in an episodic memory. The EDISON program operates in two modes: brainstorming mode and problem-solving mode. In problem-solving mode, a goal specification is given as input and EDISON attempts to achieve the goal through plan selection and sub-goal satisfaction. A goal specification can be to alter or improve a device. Devices are represented symboli-cally, and are reasoned upon by EDISON without performing numerical computations. In brainstorming mode, EDISON starts with a device recalled from memory, and attempts to create novel devices through processes of mutation, generalization and analogical reason-ing. The devices EDISON manipulates consist of simple, everyday mechanisms, such as mousetraps, nail clippers, can openers and doors. A goal of the EDISON project is to gain computational insight into the processes of naive physical reasoning [Hayes 78] and inven-tion [Lenat 76] which people exhibit. To do so, we must address a number of issues, includ-ing: (a) how devices are represented and manipulated without detailed mathematical rea-soning, (b) how devices are organized, indexed, and retrieved from a personal, episodic memory of devices and experiences of device use, (c) how new devices are discovered or in-vented during problem solving and/or brainstorming, and (d) how the resulting inventions are assessed for their novelty and/or ingenuity.


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  1. deBono, E. Children Solve Problems. Penguin. New York, NY. 1980.Google Scholar
  2. DeKleer, J. and J. Brown. A Qualitative Physics Based on Confluences. Artificial Intelligence. 24, 7–84, 1983.CrossRefGoogle Scholar
  3. Dyer, M. In-Depth Understanding. MIT Press, Cambridge, Massachusetts. 1983.Google Scholar
  4. Dyer, M. and M. Flowers. Automating Design Invention. Proceedings of Autofact 6 Conference. Anaheim, CA. 1984.Google Scholar
  5. Forbus, K. Qualitative Process Theory. Artificial Intelligence. 24, 85–168, 1983.CrossRefGoogle Scholar
  6. Hayes, P. The Second Naive Physics Manifesto. In Brachman& Levesque(eds). Readings in Knowledge Representation. Morgan Kaufmann, Los Altos, CA. 1985.Google Scholar
  7. Kolodner, J. Retrieval and Organizational Strategies in Conceptual Memory: A Computer Model. Lawrence Erlbaum Associates, Hillsdale, NJ. 1984.Google Scholar
  8. Lehnert, W. The Process of Question Answering. Lawrence Erlbaum Associates. Hillsdale, NJ. 1978zbMATHGoogle Scholar
  9. Lenat, D. AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search. Stanford University PhD. Palo Alto, CA. 1976.Google Scholar
  10. Lenat, D. EURISKO: A Program That Learns New Heuristics and Domain Concepts. Artificial Intelligence. 21(1,2), 61–98, 1983.CrossRefMathSciNetGoogle Scholar
  11. Rees, J. and Adams, N. T: A Dialect of LISP, or Lambda: The Ultimate Software Tool. Proceedings of the 1982 ACM Symposium on LISP and Functional Programming. August, 1982.Google Scholar
  12. Rieger, C. An Organization of Knowledge for Problem Solving and Language Comprehension. In Brachman& Levesque(eds). Readings in Knowledge Representation. Morgan Kaufmann, Los Altos, CA. 1985.Google Scholar
  13. Schank, R. Dynamic Memory. Cambridge University Press. Cambridge, England. 1982.Google Scholar
  14. Wasserman, K. and M. Lebowitz. Representing Complex Physical Objects. Cognition and Brain Theory. 6(3), 259–285, 1983.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1986

Authors and Affiliations

  • Michael G. Dyer
    • 1
  • Margot Flowers
    • 1
  • Jack Hodges
    • 1
  1. 1.Artificial Intelligence Laboratory, Computer Science DepartmentUniversity of California at Los AngelesLos AngelesUSA

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