Reinforcement Learning, Machine Learning, Monte Carlo, Data Science, Thoughts And Theory.
the right but if it falls at C1, then the policy evaluation will assign negative state or state-action values to cells around C1. If the policy is greedy or the exploration rate is very small, then the agent will never explore the reward at D2. Exploring starts One of the simplest ways to explore