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bandits

Solutions to the multi-armed bandits problems described in book Reinforcement Learning: An Introduction by Sutton and Barto.
Includes the following algorithms for learning optimal strategies (see Agents.py)-

  1. epsilon greedy algorithm
  2. softmax algorithm

Results:

![/graphs/nArmedBanditAvgRewardsComparison.png](/graphs/nArmedBanditAvgRewardsComparison.png?raw=true "varying epsilon in epsilon greedy: avg. reward vs iterations") ![/graphs/eGreedyvsSoftmax.png](/graphs/eGreedyvsSoftmax.png?raw=true "Epsilon-Greedy vs Softmax performance")

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implementation of the n-Armed bandit solutions as described in Sutton and Barto's book

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