36 search results - page 4 / 8 » Using Linear Programming for Bayesian Exploration in Markov ... |
NIPS
2001
13 years 9 months ago
2001
We present a principled and efficient planning algorithm for cooperative multiagent dynamic systems. A striking feature of our method is that the coordination and communication be...
NN
2010
Springer
13 years 2 months ago
2010
Springer
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
NIPS
2007
13 years 9 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...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
ICMLA
2009
13 years 5 months ago
2009
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...