Abstract
The problem of human-agent negotiation is still not well understood, mainly because human players are not fully rational from game theory’s perspective and thus the interaction in such context is hard to model using traditional ways. This paper proposes a novel strategy for complex human-agent negotiation – that is – multiple issues, unknown opponent preferences as well as real-time constraints. This novel strategy is able to model opponent behaviour during negotiation session and make reasonable decisions to establish agreements with human players. We analyze the results of extensive experiments, and show that it is able to outperform human counterparts, in both high and low conflictive negotiation scenarios.
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Acknowledgment
This work is supported by National Natural Science Foundation of China (Grant number: 61602391). The authors also thank to the anonymous reviewers of this article for their valuable comments.
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Yuan, L., Chen, S., Zhang, Z. (2019). A Novel Strategy for Complex Human-Agent Negotiation. In: Sun, Y., Lu, T., Xie, X., Gao, L., Fan, H. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2018. Communications in Computer and Information Science, vol 917. Springer, Singapore. https://doi.org/10.1007/978-981-13-3044-5_5
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DOI: https://doi.org/10.1007/978-981-13-3044-5_5
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