Connectionist Models for Learning Choice Behaviour in Reactive Software
Connectionist Models for Learning Choice Behaviour in Reactive Software
This paper proposes a model of reactive action selection specialised for intelligent software agents. It explores the role of connectionism in providing a computational model of adaptive action selection. Then, the general properties of a network necessary to implement reactive action selection are considered and an architecture proposed. Throughout, similarities with other action selection and connectionist architectures are highlighted. The paper concludes by exploring an application.
437-42
Joyce, Dan W.
21018c91-19aa-4547-aa19-afefae6b661a
Lewis, Paul H.
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
1999
Joyce, Dan W.
21018c91-19aa-4547-aa19-afefae6b661a
Lewis, Paul H.
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
Joyce, Dan W. and Lewis, Paul H.
(1999)
Connectionist Models for Learning Choice Behaviour in Reactive Software.
Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing.
.
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Abstract
This paper proposes a model of reactive action selection specialised for intelligent software agents. It explores the role of connectionism in providing a computational model of adaptive action selection. Then, the general properties of a network necessary to implement reactive action selection are considered and an architecture proposed. Throughout, similarities with other action selection and connectionist architectures are highlighted. The paper concludes by exploring an application.
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Published date: 1999
Venue - Dates:
Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, 1999-01-01
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 252538
URI: http://eprints.soton.ac.uk/id/eprint/252538
PURE UUID: 8e41fd8d-51c1-430d-8b3e-5162cb795acf
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Date deposited: 22 Feb 2000
Last modified: 10 Dec 2021 20:27
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Contributors
Author:
Dan W. Joyce
Author:
Paul H. Lewis
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