2108 search results - page 9 / 422 » Tracking in Reinforcement Learning |
AAMAS
2002
Springer
13 years 7 months ago
2002
Springer
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
ICMLA
2004
13 years 8 months ago
2004
We present JoSTLe, an algorithm that performs value iteration on control problems with continuous actions, allowing this useful reinforcement learning technique to be applied to p...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
In this paper, we confront the problem of applying reinforcement learning to agents that perceive the environment through many sensors and that can perform parallel actions using ...
IEAAIE
2001
Springer
13 years 11 months ago
2001
Springer
In this paper a combined use of reinforcement learning and simulated annealing is treated. Most of the simulated annealing methods suggest using heuristic temperature bounds as the...
ECML
2005
Springer
14 years 27 days ago
2005
Springer
Abstract. While direct, model-free reinforcement learning often performs better than model-based approaches in practice, only the latter have yet supported theoretical guarantees f...