Constructing belief networks to evaluate plans

Authors:
Paul E. Lehner;Christopher Elsaesser;Scott A. Musman
Affiliations:
AI Technical Center of MITRE and Systems Engineering Department, George Mason University, Fairfax, VA;AI Technical Center, The MITRE Corporation, McLean, VA;AI Technical Center, The MITRE Corporation, McLean, VA
Venue:
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Year:
1994

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Abstract

This paper examines the problem of constructing belief networks to evaluate plans produced by an knowledge-based planner. Techniques are presented for handling various types of complicating plan features. These include plans with context-dependent consequences, indirect consequences, actions with preconditions that must be true during the execution of an action, contingencies, multiple levels of abstraction, multiple execution agents with partially-ordered and temporally overlapping actions, and plans which reference specific times and time durations.