Beetle Bandit : Evaluation of a Bayesian -
نویسندگان
چکیده
A novel approach to Bayesian Reinforcement learning (RL) named Beetle has recently been presented; this approach nicely balances exploration vs. exploitation while learning is performed online. This has produced an interest into experimental results obtained from the Beetle algorithm. This thesis gives an overview of bandit problems and modi es the Beetle algorithm. The new Beetle Bandit algorithm is applied to the multi-armed bandit class of problems, thereby comparing the resulting Beetle Bandit algorithm with traditional and current Bayesian inspired approaches.
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