Current state-of?the-art spoken dialog systems are aimed at handling telephone calls to automate incoming caller requests. In this paper we explore a scenario which is symmetric t...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Coalition formation is a problem of great interest in AI, allowing groups of autonomous, rational agents to form stable teams. Furthermore, the study of coalitional stability conc...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
Several attempts have been made in the past to construct encoding schemes that allow modularity to emerge in evolving systems, but success is limited. We believe that in order to c...