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 ...
This paper argues that multiagent learning is a potential “killer application” for generative and developmental systems (GDS) because key challenges in learning to coordinate ...
The paper describes a decentralized peer-to-peer multi-agent learning method based on inductive logic programming and knowledge trading. The method uses first-order logic for model...
Abstract. Autonomous agents decide for themselves, on the basis of their beliefs, goals, etc., how to act in an environment. However, it is often the case that an agent is motivate...
Over the last decade, institutions have demonstrated that they are a powerful mechanism to make agent interactions more effective, structured, coordinated and efficient. Different...