50 search results - page 4 / 10 » Reinforcement Learning for Penalty Avoidance in Continuous S... |
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
AAAI
2006
13 years 8 months ago
2006
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
IROS
2009
IEEE
14 years 2 months ago
2009
IEEE
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
COR
2008
13 years 7 months ago
2008
Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such c...
AIIDE
2006
13 years 8 months ago
2006
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...