Wanyana, Tezira and Moodley, Deshendran (2021) An Agent Architecture for Knowledge Discovery and Evolution, Proceedings of KI 2021: Advances in Artificial Intelligence, September 27 – October 1, 2021, Online Conference, Lecture Notes in Computer Science (LNCS) book series (Also part of Lecture Notes in Artificial Intelligence (LNAI) book sub series), 12873, 241-256, Springer, Cham.
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Abstract
The abductive theory of method (ATOM) was recently proposed to describe the process that scientists use for knowledge discovery. In this paper we propose an agent architecture for knowledge discovery and evolution (KDE) based on ATOM. The agent incorporates a combination of ontologies, rules and Bayesian networks for representing different aspects of its internal knowledge. The agent uses an external AI service to detect unexpected situations from incoming observations. It then uses rules to analyse the current situation and a Bayesian network for finding plausible explanations for unexpected situations. The architecture is evaluated and analysed on a use case application for monitoring daily household electricity consumption patterns.
| Item Type: | Conference paper |
|---|---|
| Uncontrolled Keywords: | Agent architecture BDI Knowledge discovery and evolution Abductive theory of method |
| Subjects: | Computing methodologies > Artificial intelligence > Distributed artificial intelligence > Intelligent agents |
| Date Deposited: | 16 Oct 2021 10:42 |
| Last Modified: | 16 Oct 2021 10:42 |
| URI: | http://pubs.cs.uct.ac.za/id/eprint/1449 |
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