103 search results - page 1 / 21 » An Asymptotically Optimal Bandit Algorithm for Bounded Suppo... |
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...
ALT
2008
Springer
14 years 1 months ago
2008
Springer
Abstract. We consider an upper confidence bound algorithm for Markov decision processes (MDPs) with deterministic transitions. For this algorithm we derive upper bounds on the onl...
NIPS
2004
13 years 5 months ago
2004
In the multi-armed bandit problem, an online algorithm must choose from a set of strategies in a sequence of n trials so as to minimize the total cost of the chosen strategies. Wh...
LION
2010
Springer
13 years 8 months ago
2010
Springer
Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
JMLR
2010
12 years 11 months ago
2010
Bandit algorithms are concerned with trading exploration with exploitation where a number of options are available but we can only learn their quality by experimenting with them. ...