Article ID Journal Published Year Pages File Type
6862039 Knowledge-Based Systems 2018 45 Pages PDF
Abstract
In automated negotiation, one of crucial problems is how a negotiating agent evaluates the acceptability of an offer. Most evaluation methods are mainly based on utility functions that are in the form of linear or nonlinear mathematical formulas. However, in real life, it is hard for human users to input information accurately as these evaluation methods require. To this end, this paper proposes a new approach for offer evaluation, where human users are allowed to input fuzzy and indeterminate information. More specifically, we first propose a framework of prioritised Atanassov intuitionistic fuzzy constraint satisfaction problems. Then we propose a method to evaluate an offer according to the satisfaction degrees and dissatisfaction degrees of all the prioritised Atanassov intuitionistic fuzzy constraints that represent the users' fuzzy goals for a negotiation. Finally, we discuss how to make counter-offers of trade-off on the basis of the offer evaluation method proposed in this paper. When making a tradeoff, a negotiation agent considers not only a tradeoff alternative's similarity to the opponent's previous offer but also its satisfaction degree and dissatisfaction degree towards the most prioritised goal of the agent itself.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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