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* added policy_gradient, modified main, ddpg and README * fixed typo in README * removed unnecessary imports * small refactor * Use clap for picking up the subcommand to run. --------- Co-authored-by: Laurent <laurent.mazare@gmail.com>
688 B
688 B
candle-reinforcement-learning
Reinforcement Learning examples for candle.
This has been tested with gymnasium
version 0.29.1
. You can install the
Python package with:
pip install "gymnasium[accept-rom-license]"
In order to run the examples, use the following commands. Note the additional
--package
flag to ensure that there is no conflict with the candle-pyo3
crate.
For the Policy Gradient example:
cargo run --example reinforcement-learning --features=pyo3 --package candle-examples -- pg
For the Deep Deterministic Policy Gradient example:
cargo run --example reinforcement-learning --features=pyo3 --package candle-examples -- ddpg