Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
12-2006
Abstract
This paper presents motivations and current related work in the field of plan learning. Additionally, two approaches that achieve plan learning are presented. The two presented approaches are centred on the BDI framework of agency and have particular focus on plans, which, alongside goals, are the means to fulfil intentions in most pragmatic and theoretical realisations of the BDI framework. The first approach is a hybrid architecture that combines a BDI plan extractor and executor with a generic low-level learner. The second approach uses hypotheses to suggest incremental refinements of a priori plans. Both approaches achieve plan generation that is a result of experiential learning. We conclude by discussing issues related to these two approaches, and from other related work.
Discipline
Artificial Intelligence and Robotics
Research Areas
Data Science and Engineering
Publication
Proceedings of 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT'06, Hong Kong, December 18-22
First Page
139
Last Page
145
ISBN
9780769527482
Identifier
10.1109/IAT.2006.100
Publisher
IEEE Computer Society
City or Country
New York
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.