Follow
John Asmuth
Title
Cited by
Cited by
Year
A Bayesian sampling approach to exploration in reinforcement learning
J Asmuth, L Li, ML Littman, A Nouri, D Wingate
arXiv preprint arXiv:1205.2664, 2012
2012012
The first probabilistic track of the international planning competition
HLS Younes, ML Littman, D Weissman, J Asmuth
Journal of Artificial Intelligence Research 24, 851-887, 2005
1972005
Potential-based Shaping in Model-based Reinforcement Learning.
J Asmuth, ML Littman, R Zinkov
AAAI, 604-609, 2008
1082008
Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree search
J Asmuth, ML Littman
arXiv preprint arXiv:1202.3699, 2012
552012
Approaching Bayes-optimalilty using Monte-Carlo tree search
J Asmuth, ML Littman
Proc. 21st Int. Conf. Automat. Plan. Sched., Freiburg, Germany, 2011
282011
Model-based Bayesian reinforcement learning with generalized priors
JT Asmuth
Rutgers The State University of New Jersey, School of Graduate Studies, 2013
32013
Pac-mdp reinforcement learning with bayesian priors
J Asmuth, L Li, ML Littman, A Nouri, D Wingate
12009
BFS3 Proof of Optimality
J Asmuth, M Littman
Rutgers University, 2011
2011
RLMario: A New Reinforcement Learning Domain
J Asmuth, C Mansley
The system can't perform the operation now. Try again later.
Articles 1–9