Gym4ReaL
Reinforcement learning algorithms can be evaluated with Gym4ReaL, a Gymnasium-based suite of realistic environments.
About Gym4ReaL
Gym4ReaL is a Gymnasium-based benchmarking suite for testing reinforcement learning algorithms on real-world scenarios. It collects a set of realistic environments, each exposing algorithms to practical challenges, and documents which characteristics and RL paradigms each environment covers.
Key features
- Ships benchmark environments including dam, elevator, microgrid, robotics feeder, trading and water distribution
- Built on Gymnasium for use with standard reinforcement learning workflows
- Environment table marks continuous states, continuous actions and partial observability
- Covers partial controllability, non-stationarity, visual input and frequency adaptation
- Lists environments supporting hierarchical, risk-averse, imitation and multi-objective RL
- Includes example code for running each environment
Best for: Reinforcement learning researchers and developers who want a Gymnasium-compatible suite of realistic environments for benchmarking algorithms.
Good for
- Open source under the Apache-2.0 license
- Environment-by-environment table documents characteristics and supported RL paradigms
- Repository provides example code and separate modules and data per environment
Gym4ReaL at a glance
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
Guides for Developer Tools
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Gym4ReaL FAQ
Which environments are included in Gym4ReaL?
The repository lists DamEnv, ElevatorEnv, MicrogridEnv, RoboFeederEnv, TradingEnv and WDSEnv, each with its own modules and data files.
What license does Gym4ReaL use?
It is released under the Apache-2.0 license; the LICENSE file contains the full terms.
How can developers contribute to Gym4ReaL?
The project asks contributors to add new environments, propose bug fixes or otherwise contribute through its Contributing Guide.
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