This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
As organization-based multiagent systems are applied to more complex problems, configuring and tuning the systems can become nearly as complex as the original problem a system wa...
Scott J. Harmon, Scott A. DeLoach, Robby, Doina Ca...
This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learni...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
This paper introduces a multi-robot cooperation approach to solve the pursuit evasion problem for mobile robots that have omnidirectional vision sensors in unknown environments. T...
Abstract. A strong research emphasis is being given towards regulating interoperable multi-agent environments through norms and institutions. We are concerned with environments in ...