Advanced Actor Critic (A2C)

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• Reinforcement Learning (RL):
  • Monte Carlo (MC) Method - Model Free Reinforcement Learning
  • Markov Decision Process (MDP)
  • Q Learning
  • State-Action-Reward-State-Action (SARSA)
  • Deep Reinforcement Learning (DRL) DeepRL
  • Distributed Deep Reinforcement Learning (DDRL)
  • Deep Q Network (DQN)
  • Evolutionary Computation / Genetic Algorithms
  • Actor Critic
    • Advanced Actor Critic (A2C)
    • Asynchronous Advantage Actor Critic (A3C)
    • Lifelong Latent Actor-Critic (LILAC)
  • Hierarchical Reinforcement Learning (HRL)
• Beyond DQN/A3C: A Survey in Advanced Reinforcement Learning | Joyce Xu - Towards Data Science
• Policy Gradient (PG)
• Proximal Policy Optimization (PPO)

A2C produces comparable performance to Asynchronous Advantage Actor Critic (A3C) while being more efficient. A2C is like A3C but without the asynchronous part; this means a single-worker variant of the A3C. Understanding Actor Critic Methods and A2C | Chris Yoon - Towards Data Science