PRODIGY4.0: The Manual and Tutorial

PRODIGY is a general-purpose problem-solving architecture that serves as a basis for research in planning, machine learning, apprentice-type knowledge-refinement interfaces, and expert systems. This document is a manual for the latest version of the PRODIGY system, PRODIGY4.0, and includes descriptions of the PRODIGY representation language, control structure, user interface, abstraction module, and other features. The tutorial style is meant to provide the reader with the ability to run PRODIGY and make use of all the basic features, as well as gradually learning the more esoteric aspects of PRODIGY4.0.

[1]  Richard Fikes,et al.  STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.

[2]  Richard Fikes,et al.  Learning and Executing Generalized Robot Plans , 1993, Artif. Intell..

[3]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[4]  Nils J. Nilsson,et al.  Principles of Artificial Intelligence , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Jaime G. Carbonell,et al.  Learning effective search control knowledge: an explanation-based approach , 1988 .

[6]  Jaime G. Carbonell,et al.  Integrating derivational analogy into a general problem-solving architecture , 1988 .

[7]  Charles Elkan,et al.  Conspiracy Numbers and Caching for Searching And/Or Trees and Theorem-Proving , 1989, IJCAI.

[8]  Oren Etzioni,et al.  Explanation-Based Learning: A Problem Solving Perspective , 1989, Artif. Intell..

[9]  Manuela Veloso.  Nonlinear problem solving using intelligent casual-commitment , 1989 .

[10]  Jaime G. Carbonell,et al.  Learning by experimentation: the operator refinement method , 1990 .

[11]  Ryszard S. Michalski,et al.  Machine learning: an artificial intelligence approach volume III , 1990 .

[12]  Oren Etzioni,et al.  PRODIGY: an integrated architecture for planning and learning , 1991, SGAR.

[13]  Craig A. Knoblock.  Automatically generating abstractions for problem solving , 1991 .

[14]  Oren Etzioni,et al.  DYNAMIC: A New Role for Training Problems in EBL , 1992, ML.

[15]  Manuela Veloso,et al.  An analysis of search techniques for a totally-ordered nonlinear planner , 1992 .

[16]  Towards the knowledge level in Soar: the role of the architecture in the use of knowledge , 1993 .

[17]  Oren Etzioni,et al.  A Structural Theory of Explanation-Based Learning , 1993, Artif. Intell..