14 search results - page 1 / 3 » Sensitive Discount Optimality: Unifying Discounted and Avera... |
ICML
1996
IEEE
14 years 5 months ago
1996
IEEE
Research in reinforcementlearning (RL)has thus far concentrated on two optimality criteria: the discounted framework, which has been very well-studied, and the averagereward frame...
ICML
2001
IEEE
14 years 5 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
AI
1998
Springer
13 years 4 months ago
1998
Springer
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
UAI
2001
13 years 6 months ago
2001
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...