Oct 19, 2023 · In this paper, we present an environment suite called Safety-Gymnasium, which encompasses safety-critical tasks in both single and multi-agent ...
Oct 15, 2023 · In this paper, we present an environment suite called Safety-Gymnasium, which encompasses safety-critical tasks in both single and multi-agent scenarios.
Safety-Gymnasium is a highly scalable and customizable Safe Reinforcement Learning (SafeRL) library. It aims to deliver a good view of benchmarking SafeRL ...
Afterward, OpenAI introduced the Safety Gym benchmark suite, a collection of high-dimensional continuous control environments incorporating safety-robot tasks.
In this paper, we present an environment suite called Safety-Gymnasium, which encompasses safety-critical tasks in both single and multi-agent scenarios, ...
In this paper, we present an environment suite called Safety-Gymnasium, which encompasses safety-critical tasks in both single and multi-agent scenarios, ...
May 30, 2024 · Safe-control-gym: A unified benchmark suite for safe learning-based control and reinforcement learning in robotics. IEEE Robotics and ...
Safe Policy Optimization (SafePO) is a comprehensive algorithm benchmark for Safe Reinforcement Learning (Safe RL).
Oct 7, 2024 · The paper presents a suite of safe reinforcement learning (SafeRL) environments and algorithms to help address the safety challenges in ...
Safety-Gymnasium is a standard API for safe reinforcement learning, and a diverse collection of reference environments.
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