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Benchmarks for Spinning Up Implementations — Spinning Up documentation
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning – arXiv Vanity
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Soft Actor-Critic — Spinning Up documentation
The RL50 Handbag
Can RL From Pixels be as Efficient as RL From State? – The Berkeley Artificial Intelligence Research Blog
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Soft Actor-Critic Algorithms and Applications | DeepAI
Offline Reinforcement Learning: How Conservative Algorithms Can Enable New Applications – The Berkeley Artificial Intelligence Research Blog
Figure 2 from Catalyst.RL: A Distributed Framework for Reproducible RL Research | Semantic Scholar
Applications of reinforcement learning in energy systems - ScienceDirect
The RL50 Handbag
PDF] SAC-RL: Continuous Control of Wheeled Mobile Robot for Navigation in a Dynamic Environment | Semantic Scholar
Offline Reinforcement Learning: How Conservative Algorithms Can Enable New Applications – The Berkeley Artificial Intelligence Research Blog
Frontiers | Comparing Deep Reinforcement Learning Algorithms' Ability to Safely Navigate Challenging Waters | Robotics and AI
SAC minitaur with the Actor-Learner API | TensorFlow Agents
PDF) Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones
Reducing Entropy Overestimation in Soft Actor Critic Using Dual Policy Network
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Does On-Policy Data Collection Fix Errors in Off-Policy Reinforcement Learning? – The Berkeley Artificial Intelligence Research Blog
Reducing Entropy Overestimation in Soft Actor Critic Using Dual Policy Network
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels | DeepAI