166 search results - page 17 / 34 » Safe exploration for reinforcement learning |
CIG
2006
IEEE
14 years 2 months ago
2006
IEEE
Abstract— This paper describes experiments using reinforcement learning techniques to compute pattern urgencies used during simulations performed in a Monte-Carlo Go architecture...
ECAI
2008
Springer
13 years 10 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. ...
NIPS
1996
13 years 10 months ago
1996
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
IJCAI
2001
13 years 10 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...
ATAL
2008
Springer
13 years 10 months ago
2008
Springer
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...