arXiv:1904.07817
Simion Zoo: A Workbench for Distributed Experimentation with Reinforcement Learning for Continuous Control Tasks
원문 초록
We present Simion Zoo, a Reinforcement Learning (RL) workbench that provides a complete set of tools to design, run, and analyze the results,both statistically and visually, of RL control applications. The main features that set apart Simion Zoo from similar software packages are its easy-to-use GUI, its support for distributed execution including deployment over graphics processing units (GPUs) , and the possibility to explore concurrently the RL metaparameter space, which is key to successful RL experimentation.
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Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity
DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
Scaling Algorithm Distillation for Continuous Control with Mamba
Reinforcement Learning via Implicit Imitation Guidance
Self-Composing Policies for Scalable Continual Reinforcement Learning
CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum
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