70 search results - page 1 / 14 » Near-Bayesian exploration in polynomial time |
ICML
2009
IEEE
15 years 11 months ago
2009
IEEE
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
ML
2002
ACM
14 years 9 months ago
2002
ACM
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
TCS
2008
14 years 10 months ago
2008
Formalized study of self-assembly has led to the definition of the tile assembly model, Previously I presented ways to compute arithmetic functions, such as addition and multiplic...
IJCAI
2001
14 years 11 months ago
2001
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
FOCS
1994
IEEE
15 years 2 months ago
1994
IEEE
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...