Deep Learning Quick Reference

Policy

Keras-RL provides an -greedy Q Policy called rl.policy.EpsGreedyQPolicy that we can use to balance exploration and exploitation. We can use rl.policy.LinearAnnealedPolicy to decay our as the agent steps forward in the world, as shown in the following code:

policy = LinearAnnealedPolicy(EpsGreedyQPolicy(), attr='eps', value_max=1., value_min=.1, value_test=.05, nb_steps=10000)

Here we're saying that we want to start with a value of 1 for and go no smaller than 0.1, while testing if our random number is less than 0.05. We set the number ...