is there a command to extract a Reward function from a predefined environment?

Hi everybody,

I am new to using Matlab and the RL toolbox.

I want to know if it is possible to extract a Reward function from a predefined environment? and to see the structure of a an environment ?

I am will be Glad to hear your suggestions

best Regards

Answer 1

[Shubham]

Hi Mohamad,

In Matlab's Reinforcement Learning Toolbox, environments are defined with certain components, including state spaces, action spaces, and the reward function. For predefined environments, the reward function is typically embedded within the step function of the environment. This step function dictates how the environment responds to an action taken by the agent, including the calculation of the reward based on the new state of the environment.

Here's a general approach to try to understand or extract the reward function logic: Navigate to the file defining the environment and look for the step function. Within this function, you should see how the reward is calculated. This approach is useful for custom environments. However, for build-in environments, there is no direct way to check for the reward function logic. Still you can find some information regarding the reward logic on documentation of that specific environment.

To understand or view the structure of an environment in Matlab, you should consider the following components:

• State Space: The set of all possible states in which the environment can exist.
• Action Space: The set of all possible actions that the agent can take.
• Reward Signal: How the reward is determined based on the actions taken by the agent and the resulting state of the environment.
• Observation and Transition Dynamics: How the environment transitions from one state to another based on the actions of the agent.

For custom environments, you define these components yourself, so you can structure and view them as you build the environment. For predefined or built-in environments, you can often find this information in the documentation. Matlab's documentation typically includes details on the state and action spaces, and sometimes on how rewards are structured.

To get an overview or specific details about an environment, you should refer to the official Matlab documentation for that environment. The documentation often includes examples, and by studying these, you can get a good understanding of how the environment is structured and operates.

For example: You can check the details about grid world environment by refer to this documentation: https://in.mathworks.com/help/reinforcement-learning/ug/create-predefined-grid-world-environments.html

[Mohamad]

Thank you very much Shubham for your elaborate explainantion