Distributed Deep Reinforcement Learning (DDRL)
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- Importance Weighted Actor-Learner Architectures: Scalable Distributed DeepRL in DMLab-30
- Decentralized: Federated & Distributed Learning
- 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
- Hierarchical Reinforcement Learning (HRL)
- Agents/Assistants ... Robotic Process Automation ... Personal Companions ... Productivity ... Email ... Negotiation ... LangChain
- Policy ... Policy vs Plan ... Constitutional AI ... Trust Region Policy Optimization (TRPO) ... Policy Gradient (PG) ... Proximal Policy Optimization (PPO)
a new, highly scalable Agent architecture for distributed training called Importance Weighted Actor-Learner Architecture that uses a new off-policy correction algorithm called V-trace.