178 search results - page 8 / 36 » Probabilistic policy reuse in a reinforcement learning agent |
AAMAS
2007
Springer
13 years 8 months ago
2007
Springer
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
KCAP
2009
ACM
14 years 3 months ago
2009
ACM
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
NN
2006
Springer
13 years 8 months ago
2006
Springer
This review considers the theoretical problems facing agents that must learn and choose on the basis of reward or reinforcement that is uncertain or delayed, in implicit or proced...
GECCO
2006
Springer
14 years 8 days ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
ATAL
2007
Springer
14 years 18 days ago
2007
Springer
The dominant existing routing strategies employed in peerto-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend o...