10 search results - page 1 / 2 » Near-optimal Regret Bounds for Reinforcement Learning |
ML
2002
ACM
13 years 4 months ago
2002
ACM
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
NIPS
2008
13 years 6 months ago
2008
COLT
2010
Springer
13 years 2 months ago
2010
Springer
Multiarmed bandit problem is a typical example of a dilemma between exploration and exploitation in reinforcement learning. This problem is expressed as a model of a gambler playi...
CORR
2010
Springer
13 years 3 months ago
2010
Springer
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
AAAI
2004
13 years 6 months ago
2004
Despite increasing deployment of agent technologies in several business and industry domains, user confidence in fully automated agent driven applications is noticeably lacking. T...