Abstract
This paper studies the problem of multi-agent planning in the environment where agents may need to cooperate in order to achieve their individual goals but they do so only if the cooperation is beneficial to each of them. We assume that each agent has a reward function and a cost function that determines the agent’s utility over all possible plans. The agents negotiate to form a joint plan through a procedure of alternating offers of joint plans and side-payments. We propose an algorithm that generates an agreement for any given planning problem and show that this agreement maximizes the gross utility and minimizes the distance to the ideal utility point.
This research was supported by the Australian Research Council through Linkage Project LP0777015.
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Huang, W., Zhang, D., Zhang, Y., Perrussel, L. (2010). Bargain over Joint Plans. In: Zhang, BT., Orgun, M.A. (eds) PRICAI 2010: Trends in Artificial Intelligence. PRICAI 2010. Lecture Notes in Computer Science(), vol 6230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15246-7_57
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DOI: https://doi.org/10.1007/978-3-642-15246-7_57
Publisher Name: Springer, Berlin, Heidelberg
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