In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
In real-life multi-agent planning problems, long-term plans will often be invalidated by changes in the environment during or after the planning process. When this happens, short-t...
Xiaoyu Mao, Adriaan ter Mors, Nico Roos, Cees Witt...
Although mental states have its own place in the definition of message semantics, social commitments have emerged as a complementing element to circumvent the limitations of usin...
Roberto A. Flores, Philippe Pasquier, Brahim Chaib...
Memory-bounded techniques have shown great promise in solving complex multi-agent planning problems modeled as DEC-POMDPs. Much of the performance gains can be attributed to pruni...
Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative f...