Abstract
Automated negotiations occur when a negotiating function is performed among intelligent agents. Although current human-to-human negotiation appears to involve multiple extremely complex issues, each automated negotiation setting is simple. In particular, the structure of issues is independent and flat in the existing automated negotiation framework. In this paper, we propose realistic negotiation frameworks for non-monotonic utility functions. The monotonicity of the utility functions is an important characteristic because if the utility function is monotonic, the issues are independent. When the issues are independent, it is useful to separate them and reach a distinct agreement for each sequentially. In addition, we propose an automated mediation protocol for multiple non-monotonic issue negotiations. This mediation protocol consists of the communications between agents and the mediator. The procedures of the mediation protocol include recognizing related issues, announcement, bidding, awarding, and expediting. We experimentally demonstrate that the proposed method results in good outcomes and greater scalability. In addition, we demonstrate that a suitable mediation strategy leads to better outcomes and scalability.
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Fujita, K. (2015). Automated Negotiations Based on Monotonic Tree Representations. In: Fujita, K., Ito, T., Zhang, M., Robu, V. (eds) Next Frontier in Agent-Based Complex Automated Negotiation. Studies in Computational Intelligence, vol 596. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55525-4_4
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DOI: https://doi.org/10.1007/978-4-431-55525-4_4
Publisher Name: Springer, Tokyo
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