Control Optimization with Reinforcement Learning
This chapter focuses on a relatively new methodology called reinforcement learning. A prerequisite for this chapter is the previous chapter. Reinforcement learning (RL) is essentially a form of simulation-based dynamic programming and is primarily used to solve Markov and semi-Markov decision problems. It is natural to wonder why the word “learning” is a part of the name then. The answer is: pioneering work in this area was done by the artificial intelligence community, which views it as a machine “learning” method.
KeywordsReinforcement Learning Bellman Equation Policy Iteration Average Reward Reinforcement Learning Algorithm
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