Constructing Belief Networks to Evaluate Plans
Artificial Intelligence
2013-02-28 v1
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.
Cite
@article{arxiv.1302.6830,
title = {Constructing Belief Networks to Evaluate Plans},
author = {Paul E. Lehner and Christopher Elsaesser and Scott A. Musman},
journal= {arXiv preprint arXiv:1302.6830},
year = {2013}
}
Comments
Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)