Learning policy constraints through dialogue

Chukwuemeka David Emele; Timothy J Norman; Frank Guerin; Simon Parsons

Learning policy constraints through dialogue

Chukwuemeka David Emele, Timothy J Norman, Frank Guerin, Simon Parsons

Computing Science

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

1 Citation (Scopus)

8 Downloads (Pure)

Abstract

An understanding of the policy and resource availability constraints under which others operate is important for effectively developing and resourcing plans in a multi-agent context. Such constraints (or norms) are not necessarily public knowledge, even within a team of collaborating agents. What is required are mechanisms to enable agents to keep track of who might have and be willing to provide the resources required for enacting a plan by modeling the policies of others regarding resource use, information provision, etc. We propose a technique that combines machine learning and argumentation for identifying and modeling the policies of others. Furthermore, we demonstrate the utility of this novel combination of techniques through empirical evaluation.

Original language	English
Title of host publication	Proceedings of the AAAI Fall Symposium on The Uses of Computational Argumentation
Editors	Trevor Bench-Capon, Simon Parsons, Henry Prakken
Publisher	Association for the Advancement of Artificial Intelligence
Number of pages	6
Publication status	Published - Nov 2009

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http://www.staff.science.uu.nl/~prakk101/uses/emele.pdf

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Learning policy constraints through dialogue. / Emele, Chukwuemeka David; Norman, Timothy J; Guerin, Frank et al.
Proceedings of the AAAI Fall Symposium on The Uses of Computational Argumentation. ed. / Trevor Bench-Capon; Simon Parsons; Henry Prakken. Association for the Advancement of Artificial Intelligence, 2009.

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

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Learning policy constraints through dialogue

Abstract

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