16 search results - page 2 / 4 » Bounded Parameter Markov Decision Processes with Average Rew... |
JMLR
2010
13 years 4 days ago
2010
In this paper, we propose a novel adaptive step-size approach for policy gradient reinforcement learning. A new metric is defined for policy gradients that measures the effect of ...
CDC
2009
IEEE
13 years 10 months ago
2009
IEEE
— We consider decision making in a Markovian setup where the reward parameters are not known in advance. Our performance criterion is the gap between the performance of the best ...
FOCS
2007
IEEE
13 years 11 months ago
2007
IEEE
We consider a variant of the classic multi-armed bandit problem (MAB), which we call FEEDBACK MAB, where the reward obtained by playing each of n independent arms varies according...
EWRL
2008
13 years 7 months ago
2008
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
NIPS
2007
13 years 6 months ago
2007
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...