Abstract. Taxonomies in the area of Multi-Agent Systems (MAS) classify problems according to the underlying principles and assumptions of the agents’ abilities, rationality and i...
This paper proposes an efficient agent for competing in Cliff Edge (CE) environments, such as sealed-bid auctions, dynamic pricing and the ultimatum game. The agent competes in on...
Abstract. Learning in a multiagent environment is complicated by the fact that as other agents learn, the environment effectively changes. Moreover, other agents’ actions are oft...
This paper addresses distributed task allocation in complex scenarios modeled using the distributed constraint optimization problem (DCOP) formalism. We propose and evaluate a nov...
Paulo Roberto Ferreira Jr., Felipe S. Boffo, Ana L...
We propose an adaptive 1-to-many negotiation strategy for multiagent coalition formation in dynamic, uncertain, real-time, and noisy environments. Our strategy focuses on multi-is...