61 search results - page 7 / 13 » Convergence of synchronous reinforcement learning with linea... |
ECAI
2008
Springer
14 years 11 months ago
2008
Springer
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...
NIPS
2007
14 years 11 months ago
2007
Recently, we have introduced a novel approach to dynamic programming and reinforcement learning that is based on maintaining explicit representations of stationary distributions i...
61
Voted
ICPR
2006
IEEE
15 years 10 months ago
2006
IEEE
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
NIPS
1994
14 years 11 months ago
1994
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to real-world problems. Unfortun...
73
Voted
WSC
2008
14 years 12 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...