Optimal incremental preference elicitation during negotiation
Optimal incremental preference elicitation during negotiation
The last two decades have seen a growing interest in the development of automated agents that are able to negotiate on the user's behalf. When representing a user in a negotiation, it is essential for the agent to understand the user's preferences, without exposing them to elicitation fatigue. To this end, we propose a new model in which a negotiating agent may incrementally elicit the user's preference during the negotiation. We introduce an optimal elicitation strategy that decides, at every stage of the negotiation, how much additional user information to extract at a certain cost. Finally, we demonstrate the effectiveness of our approach by combining our policy with well-known negotiation strategies and show that it significantly outperforms other elicitation strategies.
3-9
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Gerding, Enrico H.
d9e92ee5-1a8c-4467-a689-8363e7743362
2015
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Gerding, Enrico H.
d9e92ee5-1a8c-4467-a689-8363e7743362
Baarslag, Tim and Gerding, Enrico H.
(2015)
Optimal incremental preference elicitation during negotiation.
Twenty-fourth International Joint Conference on Artificial Intelligence, , Buenos Aires, Argentina.
24 - 31 Jul 2015.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The last two decades have seen a growing interest in the development of automated agents that are able to negotiate on the user's behalf. When representing a user in a negotiation, it is essential for the agent to understand the user's preferences, without exposing them to elicitation fatigue. To this end, we propose a new model in which a negotiating agent may incrementally elicit the user's preference during the negotiation. We introduce an optimal elicitation strategy that decides, at every stage of the negotiation, how much additional user information to extract at a certain cost. Finally, we demonstrate the effectiveness of our approach by combining our policy with well-known negotiation strategies and show that it significantly outperforms other elicitation strategies.
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Accepted/In Press date: 2015
e-pub ahead of print date: July 2015
Published date: 2015
Venue - Dates:
Twenty-fourth International Joint Conference on Artificial Intelligence, , Buenos Aires, Argentina, 2015-07-24 - 2015-07-31
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 376474
URI: http://eprints.soton.ac.uk/id/eprint/376474
PURE UUID: ee70f249-16fe-4391-b6bb-83d44ec9d832
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Date deposited: 29 Apr 2015 13:39
Last modified: 15 Mar 2024 03:23
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Contributors
Author:
Tim Baarslag
Author:
Enrico H. Gerding
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