Abstract
This paper presents a compromising strategy based on constraint relaxation for automated negotiating agents. Automated negotiating agents have been studied widely and are one of the key technologies for the future society where multiple heterogeneous agents are collaborately and competitively acting in order to help humans perform daily activities. For example, driver-less cars will be common in the near future. Such autonomous cars will need to cooperate and also compete with each other in traffic situations. A lot of studies including international competitions have been made on negotiating agents. A principal issue is that most of the proposed negotiating agents employ an ad-hoc conceding process, where basically they are adjusting a threshold to accept their opponents’ offers. Because merely a threshold is adjusted, it is very difficult to show how and what the agent conceded even after agreement has been reached. To address this issue, we describe an explainable concession process we propose using a constraint relaxation process. In the process, an agent changes its belief that it should not believe a certain constraint so that it can accept its opponent’s offer. We also describe three types of compromising strategies we propose. Experimental results demonstrate that these strategies are efficient.
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Okuhara, S., Ito, T. (2019). A Compromising Strategy Based on Constraint Relaxation for Automated Negotiating Agents. In: Nayak, A., Sharma, A. (eds) PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. Lecture Notes in Computer Science(), vol 11670. Springer, Cham. https://doi.org/10.1007/978-3-030-29908-8_53
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