A Probabilistic Model of Plan Recognition
Abstract
Plan-recognition requires the construction of possible plans which could explain a set of observed actions, and then selecting one or more of them as providing the belt explanation. In this paper we present a formal model of the latter process based upon probability theory. Our model consists of a knowledge-base of facts about the world expressed in a first-order language, and rules for using that knowledge-base to construct a Bayesian network. The network is then evaluated to find the plans with the highest probability.
Cite
Text
Charniak and Goldman. "A Probabilistic Model of Plan Recognition." AAAI Conference on Artificial Intelligence, 1991.Markdown
[Charniak and Goldman. "A Probabilistic Model of Plan Recognition." AAAI Conference on Artificial Intelligence, 1991.](https://mlanthology.org/aaai/1991/charniak1991aaai-probabilistic/)BibTeX
@inproceedings{charniak1991aaai-probabilistic,
title = {{A Probabilistic Model of Plan Recognition}},
author = {Charniak, Eugene and Goldman, Robert P.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1991},
pages = {160-165},
url = {https://mlanthology.org/aaai/1991/charniak1991aaai-probabilistic/}
}