A comparison of plan-based and abstract MDP reward shaping

Two different methods for reward shaping are compared; plan-based, in which an agent is provided with a plan and extra rewards are given according to the steps of the plan the agent satisfies, and reward shaping via abstract Markov decision process (MDPs), inwhich an abstract high-level MDP of the environment is solved and the resulting value function is used to shape the agent.