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What is the relationship between planning and reinforcement learning?

  • A.Reinforcement learning is a special case of classical planning
  • B.The two solve entirely unrelated classes of problem
  • C.Planning applies to discrete and learning to continuous problems
  • D.Planning assumes a known model; learning acquires one by acting

Answer: D

Both seek a course of action maximising some objective, and the difference is whether the transition model is given or must be learned from experience. Model based reinforcement learning sits between them by learning a model and then planning with it. Neither contains the other, both handle discrete and continuous cases. Placing two apparently distinct fields on a single axis, according to what is known in advance, makes the relationship between them immediately clear.

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