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@DenisDrobyshev DenisDrobyshev released this 13 Jul 23:21
· 37 commits to main since this release
v0.2.0
a43bc7a

Highlights

Renamed to decisionrl — one name everywhere (pip install decisionrl, import decisionrl). Breaking: update imports reinforce.* → decisionrl.*.

Repositioned around applied RL — reinforcement learning for operational decisions (pricing, inventory, energy, queues, supply chains), each environment shipped with the classic operations-research baseline so a learned policy can be proved better, not just asserted.

Added

  • Four applied environments — DynamicPricing, QueueAdmissionControl, EnergyMicrogrid, SupplyChain — bringing the total to 18 environments (6 applied), each with a baseline and a learning test.
  • examples/applied_rl_demo.py: trains all six applied tasks and prints the learned-vs-baseline proof table (RL beats the naive baseline on five, recovers the base-stock optimum on inventory).
  • Baseline comparison harness vs Stable-Baselines3 (examples/benchmark_vs_baselines.py).
  • TRPO, meta-RL (RL²), and BernoulliBandit.

Changed

  • DistributedActorLearner gained a configurable recv_timeout (no more deadlock on a crashed actor).
  • README, banner and docs repositioned around applied RL. 31 algorithms, 345 tests.

Full details in CHANGELOG.md.

Full Changelog: https://github.com/DenisDrobyshev/decisionrl/commits/v0.2.0

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