In this paper we propose a multiagent architecture for implementing concurrent reinforcement learning, an approach where several agents, sharing the same environment, perceptions ...
Multi-agent systems comprise multiple, deliberative agents embedded in and recreating patterns of interactions. Each agent’s execution consumes considerable storage and calculat...
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
We report on an investigation of the learning of coordination in cooperative multi-agent systems. Specifically, we study solutions that are applicable to independent agents i.e. ...
Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. ...
Abstract. Betty’s Brain is a teachable agent system in the domain of river ecosystems that combines learning by teaching and self-regulation strategies to promote deep learning a...