The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents

Nick Lacey; Mark Lee

doi:10.1007/3-540-44826-8_14

The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents

Nick Lacey, Mark Lee

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

The purpose of this research is to show the relevance of philosophical theories to agent knowledge base (AKB) design, implementation, and behaviour. We will describe how artificial agent designers face important problems that philosophers have been working on for centuries. We will then show that it is possible to design different agents to be explicitly based on different philosophical approaches, and that doing so increases the range of agent behaviour exhibited by the system. We therefore argue that alternative, sometimes counter-intuitive, conceptions of the relationship between an agent and its environment may offer a useful starting point when considering the design of an agent knowledge base.

Original language	English
Title of host publication	Adaptive Agents and Multi-Agent Systems
Subtitle of host publication	Adaptation and Multi-Agent Learning
Editors	Eduardo Alonso, Daniel Kudenko, Dimitar Kazakov
Publisher	Springer Nature
Pages	216-238
ISBN (Electronic)	978-3-540-44826-6
ISBN (Print)	978-3-540-40068-4
DOIs	https://doi.org/10.1007/3-540-44826-8_14
Publication status	Published - 2003

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title = "The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents",

abstract = "The purpose of this research is to show the relevance of philosophical theories to agent knowledge base (AKB) design, implementation, and behaviour. We will describe how artificial agent designers face important problems that philosophers have been working on for centuries. We will then show that it is possible to design different agents to be explicitly based on different philosophical approaches, and that doing so increases the range of agent behaviour exhibited by the system. We therefore argue that alternative, sometimes counter-intuitive, conceptions of the relationship between an agent and its environment may offer a useful starting point when considering the design of an agent knowledge base.",

author = "Nick Lacey and Mark Lee",

note = "N.J. Lacey and M.H. Lee, “The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents”, Springer-Verlag Lecture Notes on Artificial Intelligence, Vol 2636 on Adaptive Agents and Multi-Agent Systems, 2002.",

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N2 - The purpose of this research is to show the relevance of philosophical theories to agent knowledge base (AKB) design, implementation, and behaviour. We will describe how artificial agent designers face important problems that philosophers have been working on for centuries. We will then show that it is possible to design different agents to be explicitly based on different philosophical approaches, and that doing so increases the range of agent behaviour exhibited by the system. We therefore argue that alternative, sometimes counter-intuitive, conceptions of the relationship between an agent and its environment may offer a useful starting point when considering the design of an agent knowledge base.

AB - The purpose of this research is to show the relevance of philosophical theories to agent knowledge base (AKB) design, implementation, and behaviour. We will describe how artificial agent designers face important problems that philosophers have been working on for centuries. We will then show that it is possible to design different agents to be explicitly based on different philosophical approaches, and that doing so increases the range of agent behaviour exhibited by the system. We therefore argue that alternative, sometimes counter-intuitive, conceptions of the relationship between an agent and its environment may offer a useful starting point when considering the design of an agent knowledge base.

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PB - Springer Nature

ER -

The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents

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