# Optimal algorithm for solving n-armed bandit problems?

I've read about a number of algorithms for solving n-armed bandit problems like $\epsilon$-greedy, softmax, and UCB1, but I'm having some trouble sorting through what approach is best for minimizing regret.

Is there a known optimal algorithm for solving the n-armed bandit problem? Is there a choice of algorithm that seems to perform best in practice?

• Presumably there is not a recognised optimal solution, as otherwise the Wikipedia page would say so and there would not be an experimental Sourceforge page May 11 '11 at 20:17
• Shouldn't this be on Theoretical Computer Science SE?
– user88
May 12 '11 at 6:31
• @mbq since reinforcement learning is a branch of machine learning, I don't think so ;) May 12 '11 at 14:18
• @steffen Sure, the name seemed "tcsy".
– user88
May 12 '11 at 14:48
• @mbq I don't get it. What does "tscy" mean ? May 13 '11 at 8:28