DagSemProc.05051.3.pdf
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An Architecture for Rational Agents
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Dagstuhl Seminar Proceedings, Volume 5051
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2006-01-19
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John W. Lloyd and Tim D. Sears. An Architecture for Rational Agents. In Probabilistic, Logical and Relational Learning - Towards a Synthesis. Dagstuhl Seminar Proceedings, Volume 5051, pp. 1-16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)
https://doi.org/10.4230/DagSemProc.05051.3
https://doi.org/10.4230/DagSemProc.05051.3
Abstract
This paper is concerned with designing architectures for rational agents.
In the proposed architecture, agents have belief bases that are theories
in a multi-modal, higher-order logic.
Belief bases can be modified by a belief acquisition algorithm
that includes both symbolic, on-line learning and conventional knowledge base
update as special cases.
A method of partitioning the state space of the agent in two different ways
leads to a Bayesian network and associated influence diagram for selecting actions.
The resulting agent architecture exhibits a tight integration between logic,
probability, and learning.
This approach to agent architecture is illustrated by a user agent
that is able to personalise its behaviour according to the user's
interests and preferences.
Keywords
- Rational agent
- agent architecture
- belief base
- Bayesian networks
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