This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
Abstract. This paper describes the application of a decentralised coordination algorithm, called Collaborative Reinforcement Learning (CRL), to two different distributed system pr...
Jim Dowling, Raymond Cunningham, Anthony Harringto...
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
Masoud Asadpour, Majid Nili Ahmadabadi, Roland Sie...
Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent’s ability to learn useful behaviors by making intelligent use of the kn...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...