Abstract
Cooperation and negotiation are important elements of human interaction within extensive, flatly organized, mixed human-machine societies. Any sophisticated artificial intelligence cannot be complete without them. Multi-agent system with dynamic locally independent agents, that interact in a distributed way is inevitable in majority of modern applications. Here we consider a modified Ultimatum game (UG) for studying negotiation and cooperation aspects of decision making. The manuscript proposes agent’s optimizing policy using Markov decision process (MDP) framework, which covers implicit negotiation (in contrast with explicit schemes as in [5]). The proposed solution replaces the classical game-theoretical design of agents’ policies by an adaptive MDP that is: (i) more realistic with respect to the knowledge available to individual players; (ii) provides a first step towards solving negotiation essential in conflict situations.
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The research has been supported by the project GA16-09848S, LTC 18075 and EU-Cost Action 16228.
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Homolová, J., Zugarová, E., Kárný, M., Guy, T.V. (2018). On Decentralized Implicit Negotiation in Modified Ultimatum Game. In: Belardinelli, F., Argente, E. (eds) Multi-Agent Systems and Agreement Technologies. EUMAS AT 2017 2017. Lecture Notes in Computer Science(), vol 10767. Springer, Cham. https://doi.org/10.1007/978-3-030-01713-2_25
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