Plan-then-compile architectures

Authors:
Tom M. Mitchell
Affiliations:
-
Venue:
ACM SIGART Bulletin
Year:
1991

Citing 1
Cited 2

Explanation-based learning: a problem solving perspective

Artificial Intelligence

Realizing believable agents: an integration of the author-based and the model-based approaches

AI Communications
Data mining techniques for robocup soccer agents

AIS-ADM 2005 Proceedings of the 2005 international conference on Autonomous Intelligent Systems: agents and Data Mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

Several architectures have recently been developed which integrate planning, reacting, and knowledge compilation learning, in order to improve system reactivity while retaining system flexibility. This paper assesses strengths and weaknesses of such Plan-Then-Compile architectures, by analyzing one such architecture, Theo-Agent [Mitchell 90]. We describe capabilities and limitations of the Theo-Agent, and use these to try to understand the generic capabilities and limits of Plan-Then-Compile architectures more generally.