Difference between revisions of "Proximal Policy Optimization (PPO)"
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* [https://arxiv.org/abs/1707.06347 Proximal policy optimization algorithms | J. Schulman, F. Wolski, P. Dhariwal, A. Radford & O. Klimov 2017] | * [https://arxiv.org/abs/1707.06347 Proximal policy optimization algorithms | J. Schulman, F. Wolski, P. Dhariwal, A. Radford & O. Klimov 2017] | ||
* [[Deep Reinforcement Learning (DRL)]] | * [[Deep Reinforcement Learning (DRL)]] | ||
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* [[Reinforcement Learning (RL)]]: | * [[Reinforcement Learning (RL)]]: | ||
** [[Monte Carlo]] (MC) Method - Model Free Reinforcement Learning | ** [[Monte Carlo]] (MC) Method - Model Free Reinforcement Learning | ||
Revision as of 16:25, 16 April 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Policy ... Policy vs Plan ... Constitutional AI ... Trust Region Policy Optimization (TRPO) ... Policy Gradient (PG) ... Proximal Policy Optimization (PPO)
- Proximal policy optimization algorithms | J. Schulman, F. Wolski, P. Dhariwal, A. Radford & O. Klimov 2017
- Deep Reinforcement Learning (DRL)
- 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
- Hierarchical Reinforcement Learning (HRL)
- Generative AI ... Conversational AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's Bing ... You ...Google's Bard ... Baidu's Ernie
- Assistants ... Hybrid Assistants ... Agents ... Negotiation ... HuggingGPT ... LangChain
- Natural Language Processing (NLP) ...Generation ...LLM ...Tools & Services
