Difference between revisions of "Proximal Policy Optimization (PPO)"
| Line 10: | Line 10: | ||
* [[Deep Reinforcement Learning (DRL)]] | * [[Deep Reinforcement Learning (DRL)]] | ||
* [[Policy Gradient (PG)]] | * [[Policy Gradient (PG)]] | ||
| + | * [[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)]] | ||
| + | |||
<youtube>5P7I-xPq8u8</youtube> | <youtube>5P7I-xPq8u8</youtube> | ||
Revision as of 16:17, 3 July 2020
Youtube search... ...Google search
- Deep Reinforcement Learning (DRL)
- Policy Gradient (PG)
- 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)
