Safety Gym

Safety Gym is an open-source reinforcement learning benchmark designed to help researchers and developers train agents that act safely while learning. It provides standardized environments with safety constraints, making it easier to evaluate and compare algorithms that must balance performance with risk.

Features of Safety Gym:

• Standardized benchmark environments for safe reinforcement learning.
• Explicit safety costs and constraints to evaluate agent behavior.
• Physics-based simulation environments for realistic interactions.
• Support for training and evaluating constrained RL algorithms.
• Clear metrics for comparing safety and performance trade-offs.
• Widely used in academic and applied RL research.
• Extensible framework for creating custom tasks and constraints.
• Designed to integrate with popular RL libraries and workflows.

Safety-GYM Usage Instructions:

$ sudo su
$ cd /opt
$ conda activate safety_gym
$ cd safety-gymnasium
$ To check version: test-safety-gym
$ Get started with Safety Gym, a simple benchmark for training safe reinforcement learning agents.
    

Disclaimer: Safety Gym is open-source software distributed under its respective open-source license. It is developed and maintained by the research community and is not affiliated with any commercial entities unless explicitly stated. The software is provided "as is," without warranties or guarantees of any kind. Users are responsible for their use of the software and should ensure compliance with applicable laws and licenses.