In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
From a multiagent viewpoint, a workflow is a dynamic set of tasks performed by a set of agents to reach a shared goal. We show herein that commitments among agents can be used to ...
The rapid growth of service coordination languages creates a need for methodological support for coordination design. Coordination design differs from workflow design because a ...
Abstract. The paper discusses a distributed approach for monitoring and diagnosing the execution of a plan where concurrent actions are performed by a team of cooperating agents. T...