We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
The problem of coalition formation when agents are uncertain about the types or capabilities of their potential partners is a critical one. In [3] a Bayesian reinforcement learnin...
Abstract. This paper introduces the notion of Run Transferable Libraries, a mechanism to pass knowledge acquired in one GP run to another. We demonstrate that a system using these ...
The field of transfer learning aims to speed up learning across multiple related tasks by transferring knowledge between source and target tasks. Past work has shown that when th...
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...