A lightweight package for running small experiments with reward shaping in reinforcement learning.
A lightweight package for running small experiments with reward shaping in reinforcement learning.
To see the API in action you can clone this notebook locally or just:
During testing, various files are created. We should add some code to clean them up :)
In the notebook an experiment is described involving a multi-armed bandit. Implement this experiment.
Some of the claims in the notebook about training graphs looking the same don't seem to be quite right. For example, the PBRS wrapper that aims for 'zero' value does, in fact, make an improvement in the small lake training. More confusingly, the 'initializing Q table' training and PBRS training don't seem to be the same- even though a paper claims they should be identical. Is this a seeding issue only or something more?
It'd be good to have docs!
Add support for specifying a seed or seeds in an Experiment for reproducibility.
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