11 search results - page 1 / 3 » An Asymptotically Optimal Algorithm for the Max k-Armed Band... |
AAAI
2006
13 years 6 months ago
2006
We present an asymptotically optimal algorithm for the max variant of the k-armed bandit problem. Given a set of k slot machines, each yielding payoff from a fixed (but unknown) d...
CP
2006
Springer
13 years 8 months ago
2006
Springer
The max k-armed bandit problem is a recently-introduced online optimization problem with practical applications to heuristic search. Given a set of k slot machines, each yielding p...
CORR
2011
Springer
12 years 12 months ago
2011
Springer
In this paper we study the online learning problem involving rested and restless multiarmed bandits with multiple plays. The system consists of a single player/user and a set of K...
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
2012
Springer
12 years 17 days ago
2012
Springer
Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit proble...