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Xudong Luo


Publications by Xudong Luo (bibliography)

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Luo, Xudong, Jennings, Nicholas R. and Shadbolt, Nigel (2006): Acquiring user tradeoff strategies and preferences for negotiating agents: A default-then-adjust method. In International Journal of Human-Computer Studies, 64 (4) pp. 304-321. http://dx.doi.org/10.1016/j.ijhcs.2005.08.001

A wide range of algorithms have been developed for various types of negotiating agents. In developing such algorithms the main focus has been on their efficiency and their effectiveness. However, this is only a part of the picture. Typically, agents negotiate on behalf of their owners and for this to be effective the agents must be able to adequately represent their owners' strategies and preferences for negotiation. However, the process by which such knowledge is acquired is typically left unspecified. To address this problem, we undertook a study of how user information about negotiation tradeoff strategies and preferences can be captured. Specifically, we devised a novel default-then-adjust acquisition technique. In this, the system firstly does a structured interview with the user to suggest the attributes that the tradeoff could be made between, then it asks the user to adjust the suggested default tradeoff strategy by improving some attribute to see how much worse the attribute being traded off can be made while still being acceptable, and, finally, it asks the user to adjust the default preference on the tradeoff alternatives. This method is consistent with the principles of standard negotiation theory and to demonstrate its effectiveness we implemented a prototype system and performed an empirical evaluation in an accommodation renting scenario. The result of this evaluation indicates the proposed technique is helpful and efficient in accurately acquiring the users' tradeoff strategies and preferences.

© All rights reserved Luo et al. and/or Academic Press

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Castro-Schez, Jose J., Jennings, Nicholas R., Luo, Xudong and Shadbolt, Nigel (2004): Acquiring domain knowledge for negotiating agents: a case of study. In International Journal of Human-Computer Studies, 61 (1) pp. 3-31. http://dx.doi.org/10.1016/j.ijhcs.2003.09.006

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 needs 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 their 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.

© All rights reserved Castro-Schez et al. and/or Academic Press

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Luo, Xudong, Jennings, Nicholas R. and Shadbolt, Nigel (2003): Knowledge-based acquisition of tradeoff preferences for negotiating agents. In: Sadeh, Norman M., Dively, Mary Jo, Kauffman, Robert J., Labrou, Yannis, Shehory, Onn, Telang, Rahul and Cranor, Lorrie Faith (eds.) Proceedings of the 5th International Conference on Electronic Commerce - ICEC 2003 September 30 - October 03, 2003, Pittsburgh, Pennsylvania, USA. pp. 138-149. http://doi.acm.org/10.1145/948005.948024

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