Hi Masoud,
To create a custom reinforcement learning environment in MATLAB, you can configure MATLAB by adding the OpenSim library using the ‘addpath’ function in MATLAB.
Then you can define the structure of the environment and load the OpenSim model.
import org.opensim.modeling.*
model = Model('model.osim');
state = model.initSystem();
Implement the core functions like the step function to update the environment and the reset function to reset the environment to its initial state.Then you can define the custom reinforcement environment using ‘rlFunctionEnv’ function and train the RL agent in the environment.
env = rlFunctionEnv(obsInfo, actInfo, 'stepFcn', 'resetFcn');
trainResults = train(agent, env, trainOpts);
To know more about the ‘rlFunctionEnv’ or ‘addpath’ function in MATLAB, you can refer the following documentations:
- https://www.mathworks.com/help/reinforcement-learning/ref/rl.env.rlfunctionenv.html
- https://www.mathworks.com/help/matlab/ref/addpath.html
Hope this will be useful.
