Simulate an RL Agent's Action — rl_action

This is a generic function used to simulate an RL agent's action given a specific decision-making policy.

rl_action_simulate(policy, values, ...)

Arguments

policy: What policy should a decision be made under? Currently supported are softmax, greedy, and epsilon-greedy.
values: A numeric vector containing the current value estimates of each action.
...: Additional arguments passed to or from specific methods, such as tau when policy = "softmax" and epsilon when policy = "epsilonGreedy".

A number representing which action will be taken given the chosen policy.