178 search results - page 7 / 36 » Probabilistic policy reuse in a reinforcement learning agent |
AAAI
2008
13 years 11 months ago
2008
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
AAAI
2007
13 years 11 months ago
2007
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
ROBOCUP
2007
Springer
14 years 2 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
AAAI
2010
13 years 10 months ago
2010
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature conv...