Difference between revisions of "Advanced Actor Critic (A2C)"
| Line 8: | Line 8: | ||
[http://www.google.com/search?q=Advanced+A2C+Actor+Critic+Reinforcement+Machine+Learning ...Google search] | [http://www.google.com/search?q=Advanced+A2C+Actor+Critic+Reinforcement+Machine+Learning ...Google search] | ||
| − | * [[Reinforcement Learning (RL)]] | + | * [[Reinforcement Learning (RL)]] |
** [[Monte Carlo]] (MC) Method - Model Free Reinforcement Learning | ** [[Monte Carlo]] (MC) Method - Model Free Reinforcement Learning | ||
** [[Markov Decision Process (MDP)]] | ** [[Markov Decision Process (MDP)]] | ||
| + | ** [[State-Action-Reward-State-Action (SARSA)]] | ||
** [[Q Learning]] | ** [[Q Learning]] | ||
| − | ** [[ | + | *** [[Deep Q Network (DQN)]] |
** [[Deep Reinforcement Learning (DRL)]] DeepRL | ** [[Deep Reinforcement Learning (DRL)]] DeepRL | ||
** [[Distributed Deep Reinforcement Learning (DDRL)]] | ** [[Distributed Deep Reinforcement Learning (DDRL)]] | ||
| − | |||
** [[Evolutionary Computation / Genetic Algorithms]] | ** [[Evolutionary Computation / Genetic Algorithms]] | ||
** [[Actor Critic]] | ** [[Actor Critic]] | ||
*** Advanced Actor Critic (A2C) | *** Advanced Actor Critic (A2C) | ||
| − | *** [[Asynchronous Advantage Actor Critic (A3C)]] | + | *** [[Asynchronous Advantage Actor Critic (A3C)]] |
*** [[Lifelong Latent Actor-Critic (LILAC)]] | *** [[Lifelong Latent Actor-Critic (LILAC)]] | ||
** [[Hierarchical Reinforcement Learning (HRL)]] | ** [[Hierarchical Reinforcement Learning (HRL)]] | ||
Revision as of 06:12, 6 July 2020
YouTube search... ...Google search
- Reinforcement Learning (RL)
- Monte Carlo (MC) Method - Model Free Reinforcement Learning
- Markov Decision Process (MDP)
- State-Action-Reward-State-Action (SARSA)
- Q Learning
- Deep Reinforcement Learning (DRL) DeepRL
- Distributed Deep Reinforcement Learning (DDRL)
- 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
