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added documentation to plotting methods and added info about monitoring, recording, plotting to usage.rst

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Chanumask
2024-03-11 09:38:23 +01:00
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docs/source/usage.rst
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@ -61,9 +61,11 @@ Evaluating the run
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If monitoring and recording are enabled, the environment states will be traced and recorded automatically.
Plotting. At the moment a plot of the evaluation score across the different episodes is automatically generated.
The EnvMonitor class acts as a wrapper for Gym environments, monitoring and logging key information during interactions,
while the EnvRecorder class records state summaries during interactions in the environment.
At the end of each run a plot displaying the step reward is generated. The step reward represents the cumulative sum of rewards obtained by all agents throughout the episode.
Furthermore a comparative plot that shows the achieved score (step reward) over several runs with different seeds or different parameter settings can be generated using the methods provided in plotting/plot_compare_runs.py.
For a more comprehensive evaluation, we recommend using the `Weights and Biases (W&B) <https://wandb.ai/site>`_ framework, with the dataframes generated by the monitor and recorder. These can be found in the run path specified in your script. W&B provides a powerful API for logging and visualizing model training metrics, enabling analysis using predefined or also custom metrics.
Indices and tables
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