Single-Player policies¶

See here the documentation: docs/Policies

List of Policies¶

Policies module : contains various (single-player) bandits algorithms:

API¶

All policies have the same interface, as described in BasePolicy, in order to use them in any experiment with the following approach:

my_policy = Policy(nbArms, *args, lower=0, amplitude=1, **kwargs)
my_policy.startGame()  # start the game
for t in range(T):
    chosen_arm_t = k_t = my_policy.choice()  # chose one arm
    reward_t     = sampled from an arm k_t   # sample a reward
    my_policy.getReward(k_t, reward_t)       # give it the the policy