The paper formalizes a distributed approach to the problem of supervising the execution of a multi-agent plan where (possibly joint) actions are executed concurrently by a team of...
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
This paper investigates a relatively new direction in Multiagent Reinforcement Learning. Most multiagent learning techniques focus on Nash equilibria as elements of both the learn...
Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent’s ability to learn useful behaviors by making intelligent use of the kn...
The impact of learning on evolution in dynamic environments undergoes recognized stages of the Baldwin Effect although its cause is not clear. To identify it experimentally, we de...