Awesome
Gym.NET
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A port of openai/gym to C#.<br>
openai/gym
OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. This is the gym open-source library, which gives you access to a standardized set of environments.
Installation
### For gym's abstract classes for RL, install:
PM> Install-Package Gym.NET
### For implemented environments, install:
PM> Install-Package Gym.NET.Environments
PM> Install-Package Gym.NET.Rendering.Avalonia
PM> Install-Package Gym.NET.Rendering.WinForm
Example
The following example runs and renders cartpole-v1 environment.
using NumSharp;
using SixLabors.ImageSharp;
using Gym.Environments;
using Gym.Environments.Envs.Classic;
using Gym.Rendering.WinForm;
CartPoleEnv cp = new CartPoleEnv(WinFormEnvViewer.Factory); //or AvaloniaEnvViewer.Factory
bool done = true;
for (int i = 0; i < 100_000; i++)
{
if (done)
{
NDArray observation = cp.Reset();
done = false;
}
else
{
var (observation, reward, _done, information) = cp.Step((i % 2)); //we switch between moving left and right
done = _done;
//do something with the reward and observation.
}
SixLabors.ImageSharp.Image img = cp.Render(); //returns the image that was rendered.
Thread.Sleep(15); //this is to prevent it from finishing instantly !
}
cp.Close();
Roadmap
-
Implement Spaces
-
Space
(base class) -
Box
-
Discrete
-
multi.*.py
-
-
Implement Env base classes
- Env(object)
- GoalEnv(Env)
-
Implement environments<br> To run an environment, see Gym.Tests
- Convert Gym.Environments to a net-standard project.
- classics
- CartPole-v1
- Compare visually against python's version
- walker2d_v3
- acrobot
- continuous_mountain_car
- mountain_car
- pendulum
- rendering
- CartPole-v1
- Mujco
- ant_v3
- half_cheetah_v3
- hopper_v3
- humanoid_v3
- humanoidstandup
- inverted_double_pendulum
- inverted_pendulum
- mujoco_env
- pusher
- reacher
- striker
- swimmer_v3
- thrower
- box2d
- bipedal_walker
- car_dynamics
- car_racing
- lunar_lander
- atari