Abstract
In human-agent automated negotiations, one of crucial problems is how a negotiating agent updates conceding strategies in the light of the new information during the course of a negotiation. To this end, this paper proposes a novel model of a seller negotiating agent, which can be used in human-agent negotiations. More specifically, it can dynamically change its conceding strategies according to the remaining time and opponents’ cooperative degree. We use type-2 fuzzy rules to determine such changes because the rules of this kind can well reflect uncertain information in human-computer negotiations. Finally, our agent is evaluated by both agent-agent and human-agent experiments.
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Notes
- 1.
It takes about two pages to display the whole algorithm. So, for the sake of space, we do not show it here but the reader can check out its details in [12].
- 2.
The methodology of the seller agent model can also be applied to a buyer agent. But in this paper, we will pay more attention in the situation where the seller is an agent with adaptive strategies, while the buyer is a human, or an agent with fixed strategies.
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Acknowledgments
This research is supported by the Bairen Plan of Sun Yat-sen University, the Natural Science Foundation of Guangdong Province, China (No.2016A030313231) and the National Fund of Social Science (No. 13BZX066).
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Zhan, J., Luo, X. (2016). Adaptive Conceding Strategies for Negotiating Agents Based on Interval Type-2 Fuzzy Logic. In: Lehner, F., Fteimi, N. (eds) Knowledge Science, Engineering and Management. KSEM 2016. Lecture Notes in Computer Science(), vol 9983. Springer, Cham. https://doi.org/10.1007/978-3-319-47650-6_18
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