Abstract
In automated negotiation, one of crucial problems is how a negotiating agent evaluates the acceptability of an offer. Most models mainly use two kinds of evaluation methods: (i) linear utility functions that depend on issues, and (ii) nonlinear utility functions that depend on crisp constraints. However, in real life, it is hard for human users to input so much and so accurate information that these evaluation methods require. To this end, this paper proposes a new approach for offer evaluation where human users are allowed to input indeterminate information. More specifically, we propose a framework of prioritised intuitionistic fuzzy constraint satisfaction problems for modelling agent’s goals. Moreover, we take both satisfaction degree and dissatisfaction degree into consideration when calculating an agent’s acceptability of an offer. Finally, we discuss how to make trade-offs via similarity measure based on intuitionistic fuzzy criteria functions.
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- 1.
The negotiation strategy is an important component of an negotiating agent. However, in this paper, the main purpose is to propose a new way of offer evaluation, rather than constructing negotiation strategies. So, we will not detail the strategies in the subsequent part of this paper.
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Acknowledgments
This research is supported by the Bairen Plan of Sun Yat-sen University and the National Fund of Social Science (No. 13BZX066).
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Zhan, J., Luo, X. (2016). Offer Evaluation and Trade-Off Making in Automated Negotiation Based on Intuitionistic Fuzzy Constraints. In: Baldoni, M., Chopra, A., Son, T., Hirayama, K., Torroni, P. (eds) PRIMA 2016: Principles and Practice of Multi-Agent Systems. PRIMA 2016. Lecture Notes in Computer Science(), vol 9862. Springer, Cham. https://doi.org/10.1007/978-3-319-44832-9_12
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