Benchmarks

Tianshou’s algorithm implementations lead to state-of-the-art results on standard benchmarks.

An efficient parallel implementation for evaluating algorithms on mujoco or atari is in benchmark/run_benchmark.py. It can easily be adapted for custom benchmarks as well. The reported results are thus completely reproducible.

The evaluation code uses Tianshou’s integration with the rliable framework, which supports best practices for trustworthy RL evaluation. Each experiment is conducted under 5 random seeds, we report the interquartile mean (IQM) and 95% confidence intervals over these seeds.