51 search results - page 3 / 11 » Improving Approximate Value Iteration Using Memories and Pre... |
UAI
2008
13 years 6 months ago
2008
Bounded policy iteration is an approach to solving infinitehorizon POMDPs that represents policies as stochastic finitestate controllers and iteratively improves a controller by a...
AAMAS
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
CORR
2010
Springer
13 years 3 months ago
2010
Springer
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
ATAL
2005
Springer
13 years 10 months ago
2005
Springer
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
ECAI
2008
Springer
13 years 6 months ago
2008
Springer
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...