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Pros and Cons of Actor-Critic Method
Advantages: It could use one step adjustment, which leads to much faster training process compared to traditional policy-gradient method. Disadvantages: Actors' actions highly depend on critics' value. However, it's already hard to reach a convergence of the critics. It's even hard to reach the convergence with the actors. If there is no enough data, it may lead to a under-fitting.
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Pros and Cons of Actor-Critic Method
DQN
DDPG
Role of the Critic in Advantage Function Calculation
Robotic Chef Learning Paradigm
An autonomous agent is at a specific position in a grid world and must choose one of four directions to move (up, down, left, right). A purely value-based agent would estimate the long-term value of moving in each of the four directions and deterministically choose the direction with the highest estimated value. How does the decision-making process of an agent using an actor-critic method fundamentally differ in this same situation?
Definition of the Advantage Function
Training of Reward Models
In a reinforcement learning framework that separates the decision-making process from the evaluation process, there are two key components. Match each component to its primary function and the nature of its output.
Advantage Actor-Critic (A2C) Method