TY - GEN
T1 - Towards a quality assessment method for learning preference profiles in negotiation
AU - Hindriks, Koen V.
AU - Tykhonov, Dmytro
PY - 2010/1/1
Y1 - 2010/1/1
N2 - In automated negotiation, information gained about an opponent's preference profile by means of learning techniques may significantly improve an agent's negotiation performance. It therefore is useful to gain a better understanding of how various negotiation factors influence the quality of learning. The quality of learning techniques in negotiation are typically assessed indirectly by means of comparing the utility levels of agreed outcomes and other more global negotiation parameters. An evaluation of learning based on such general criteria, however, does not provide any insight into the influence of various aspects of negotiation on the quality of the learned model itself. The quality may depend on such aspects as the domain of negotiation, the structure of the preference profiles, the negotiation strategies used by the parties, and others. To gain a better understanding of the performance of proposed learning techniques in the context of negotiation and to be able to assess the potential to improve the performance of such techniques a more systematic assessment method is needed. In this paper we propose such a systematic method to analyse the quality of the information gained about opponent preferences by learning in single-instance negotiations. The method includes measures to assess the quality of a learned preference profile and proposes an experimental setup to analyse the influence of various negotiation aspects on the quality of learning. We apply the method to a Bayesian learning approach for learning an opponent's preference profile and discuss our findings.
AB - In automated negotiation, information gained about an opponent's preference profile by means of learning techniques may significantly improve an agent's negotiation performance. It therefore is useful to gain a better understanding of how various negotiation factors influence the quality of learning. The quality of learning techniques in negotiation are typically assessed indirectly by means of comparing the utility levels of agreed outcomes and other more global negotiation parameters. An evaluation of learning based on such general criteria, however, does not provide any insight into the influence of various aspects of negotiation on the quality of the learned model itself. The quality may depend on such aspects as the domain of negotiation, the structure of the preference profiles, the negotiation strategies used by the parties, and others. To gain a better understanding of the performance of proposed learning techniques in the context of negotiation and to be able to assess the potential to improve the performance of such techniques a more systematic assessment method is needed. In this paper we propose such a systematic method to analyse the quality of the information gained about opponent preferences by learning in single-instance negotiations. The method includes measures to assess the quality of a learned preference profile and proposes an experimental setup to analyse the influence of various negotiation aspects on the quality of learning. We apply the method to a Bayesian learning approach for learning an opponent's preference profile and discuss our findings.
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U2 - 10.1007/978-3-642-15237-5_4
DO - 10.1007/978-3-642-15237-5_4
M3 - Conference contribution
AN - SCOPUS:77956107114
SN - 3642152368
SN - 9783642152368
T3 - Lecture Notes in Business Information Processing
SP - 46
EP - 59
BT - Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis - AAMAS Workshop, AMEC 2008, and AAAI Workshop, TADA 2008, Revised Selected Papers
PB - Springer/Verlag
T2 - 10th Workshop on Agent-Mediated Electronic Commerce, AMEC-X, Co-located with AAMAS 2008 and the 6th Workshop on Trading Agent Design and Analysis, TADA, Co-located with AAAI 2008
Y2 - 14 July 2008 through 14 July 2008
ER -