Applying problem solving methods for process knowledge acquisition, representation, and reasoning

ABSTRACT

In this paper we present an approach towards knowledgeacquisition of process knowledge for the natural sciences.The work has been conducted within Project Halo, whichis creating advanced knowledge authoring and questionanswering systems for the natural sciences. An analysis of AP®-level questions for Biology, Chemistry and Physicsuncovered that process knowledge is the single most frequenttype of knowledge required. Thus, we developedmeans to acquire process knowledge, to formally representit, and to reason about it in order to answer novel questionsabout the domains.All these tasks are supported by an abstract process metamodel.It provides the terminology for user-tailored processdiagrams, which are automatically translated into executableFLogic code. The meta-model and the code generationare based on the notion of Problem Solving Methods(PSM) which represent an abstract formalization of thereasoning strategies needed for processes.

REFERENCES

• 1: Mike Uschold , Martin King , Stuart Moralee , Yannis Zorgios, The Enterprise Ontology, The Knowledge Engineering Review, v.13 n.1, p.31-89, March 1998 [doi>10.1017/S0269888998001088]
• 2: Ohno-Machado, L., Gennari, J., Murphy, S., Jain, N., Tu, S., Oliver, D., Pattison--Gordon, E. "The GuideLine Interchange Format: A Model for Representing Guidelines", Journal of the American Medical Informatics Association, 5(4):357--372, 1998.
• 3: E. Motta, Reusable Components for Knowledge Modelling: Case Studies in Parametric Design Problem Solving, IOS Press, Amsterdam, The Netherlands, 1999
• 4: B. J. Wielinga , A. Th. Schreiber , J. A. Breuker, KADS: a modelling approach to knowledge engineering, Knowledge Acquisition, v.4 n.1, p.5-53, March 1992 [doi>10.1016/1042-8143(92)90013-Q]
• 5: Bob Wielinga , Walter Van de Velde , Guus Schreiber , Hans Akkermans, Towards a unification of knowledge modelling approaches, Second generation expert systems, Springer-Verlag New York, Inc., Secaucus, NJ, 1993
• 6: Fernández--López M., Gómez--Pérez A., Juristo N. (1997) METHONTOLOGY: From Ontological Art Towards Ontological Engineering. Spring Symposium on Ontological Engineering of AAAI. Stanford University, California, pp 33--40
• 7: Friedland, N. Allen, P., Matthews, G., Witbrock, M., Baxter, D., Curtis, J., Shepard, B., Miraglia, P., Angele, J., Staab, S., Moench, E., Oppermann, H., Wenke, D., Israel, D., Chaudhri, V., Porter, B., Barker, K., Fan, J., Chaw, S., Yeh, P., Tecuci, D., & Clark, P. (2004). Project Halo: Towards a digital Aristotle. AI Magazine, 25(4), 29--48.
• 8: Michael Kifer , Georg Lausen , James Wu, Logical foundations of object-oriented and frame-based languages, Journal of the ACM (JACM), v.42 n.4, p.741-843, July 1995 [doi>10.1145/210332.210335]
• 9: Zenon W. Pylyshyn, Robot's Dilemma: The Frame Problem in Artificial Intelligence, Greenwood Publishing Group Inc., Westport, CT, 1987
• 10: Brown, T., Lemay, H., Bursten, B., Burdge, J. Chemistry: The Central Science, Prentice Hall, 9th edition, 2002.
• 11: Campbell, N., Reece, J. Biology, Pearson Higher Education, 6th edition, 2001.
• 12: Serway, R., Faughn, J. College Physics, Brooks Cole, 6th edition, 2003.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search

General Terms:
Algorithms, Design, Human Factors, Languages, Measurement, Performance, Theory, Verification

Keywords:
DarkMatter, FLogic, frame problem, problem solving methods, process knowledge, project halo, semantic web, usability