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Acquiring domain knowledge for negotiating agents: a case study

Acquiring domain knowledge for negotiating agents: a case study
Acquiring domain knowledge for negotiating agents: a case study
In this paper, we employ the fuzzy repertory table technique to acquire the necessary domain knowledge for software agents to act as sellers and buyers using a bilateral, multi-issue negotiation model that can achieve optimal results in semi-competitive environments. In this context, the seller's domain knowledge that need to be acquired is the rewards associated with the products and restrictions attached to their purchase. The buyer's domain knowledge that is acquired is the requirements and preferences on the desired products. The knowledge acquisition methods we develop involve constructing three fuzzy repertory tables and their associated distinctions matrixes. The first two are employed to acquire the seller agent's domain knowledge; and the third one is used, together with an inductive machine learning algorithm, to acquire the domain knowledge for the buyer agent.
3-31
Castro-Schez, J.J.
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Jennings, N. R.
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Luo, X.
a883c26d-debf-44ce-9240-df70f65ddf53
Shadbolt, N.
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Castro-Schez, J.J.
4d9da220-d4fa-45b5-93ac-38f98e75f8a9
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Luo, X.
a883c26d-debf-44ce-9240-df70f65ddf53
Shadbolt, N.
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7

Castro-Schez, J.J., Jennings, N. R., Luo, X. and Shadbolt, N. (2004) Acquiring domain knowledge for negotiating agents: a case study. International Journal of Human-Computer Studies, 61 (1), 3-31.

Record type: Article

Abstract

In this paper, we employ the fuzzy repertory table technique to acquire the necessary domain knowledge for software agents to act as sellers and buyers using a bilateral, multi-issue negotiation model that can achieve optimal results in semi-competitive environments. In this context, the seller's domain knowledge that need to be acquired is the rewards associated with the products and restrictions attached to their purchase. The buyer's domain knowledge that is acquired is the requirements and preferences on the desired products. The knowledge acquisition methods we develop involve constructing three fuzzy repertory tables and their associated distinctions matrixes. The first two are employed to acquire the seller agent's domain knowledge; and the third one is used, together with an inductive machine learning algorithm, to acquire the domain knowledge for the buyer agent.

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Published date: 2004
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 258843
URI: http://eprints.soton.ac.uk/id/eprint/258843
PURE UUID: 3bdb591d-64b7-4b22-b4a4-884500c798ef

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Date deposited: 06 Sep 2004
Last modified: 14 Mar 2024 06:13

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Contributors

Author: J.J. Castro-Schez
Author: N. R. Jennings
Author: X. Luo
Author: N. Shadbolt

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