Policy Optimization

Policy Optimization deals with algorithms that, unlike value iteration/policy iteration/online planning which uses a surrogate (like value function or some future discounted reward) to calculate a policy, directly optimizes against policy parameters \(\theta\) for a policy \(\pi_{\theta}\).

• Local Policy Search (aka Hooke-Jeeves Policy Search)
• Genetic Policy Search
• Cross Entropy Method
• Policy Gradient, Regression Gradient and Likelyhood Ratio Gradient
• Reward-to-Go