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Agents that Reason and Learn

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Date

2003

Authors

Lloyd, John

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Publisher

Springer

Abstract

The issues related to designing architectures for agents that need to be able to adapt to changing circumstances during deployment are discussed. This research is being carried out in the context of the Smart Internet technology Cooperative Research Center. The first attempt in this project at an architecture involves integrating BDI agent architectures for the reasoning component and reinforcement learning for the learning component. In the research, the learning system used to approximate the Q-function is ALKEMY, a decision-tree learning system with a foundation in higher-order logic.

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Citation

URI

http://hdl.handle.net/1885/86117

Collections

ANU Research Publications

Source

Inductive Logic Programming: Proceedings of 13th International Conference, ILP 2003

Type

Conference paper

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DOI

Restricted until

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