beobench 0.4.3

Beobench is a toolbox for benchmarking reinforcement learning (RL) algorithms on building energy optimisation (BEO) problems.

A toolbox for benchmarking reinforcement learning (RL) algorithms on building energy optimisation (BEO) problems. Beobench tries to make working on RL for BEO easier: it provides simple access to existing libraries defining BEO problems (such as BOPTEST) and provides a large set of pre-configured RL algorithms. Beobench is not a gym library itself - instead it leverages the brilliant work done by many existing gym-type projects and makes their work more easily accessible.

For more information go to the documentation and the GitHub code repository.

History

0.4.3 (2022-04-00)

• Feature: enable easy access to standard configs via util method

• Feature: add non-normalised observations to info in energym integration (#62)

• Feature: enable logging full episode data from RLlib and adding this data to wandb (#62)

• Feature: ship integrations with package improving image build times (#44)

• Feature: add wandb logging support for random agent script (#59)

• Feature: add rule-based agent script based on energym controller (#60)

• Fix: add importlib-resources backport package to requirements

• Fix: allow users to disable reset() method in energym envs (#43)

• Aux: add automatic deployment of PyPI package via GitHub actions (#50)

• Aux: add tests and automatic checks on PRs (#25)

0.4.2 (2022-04-04)

• Feature: defining all relevant options/kwargs of CLI an API is now supported yaml files (#54)

• Feature: allow multiple configs to be given to both CLI (giving multiple -c options) and Python API (as a list) (#51)

• Fix: adapted Energym env reset() method to avoid triggering long warm-up times with additional simulation runs (#43)

• Fix: enable container build even if prior build failed midway and left artifacts

0.4.1 (2022-03-30)

• Feature: enable package extras to be given in development mode

• Feature: add support for arm64/aarch64-based development by forcing experiment containers to run as amd64 containers on those systems (#32)

• Fix: add gym to extended package requirements

0.4.0 (2022-03-28)

• Make dependencies that are only used inside experiment/gym containers optional (for all dependencies install via pip install beobench[extended])

• Add two part experiment image build process so that there is shared beobench installation dockerfile

• Add support for yaml config files (!)

• Overhaul of documentation, including new envs page and new theme

• Enable RLlib free experiment containers when not required

• Add beobench_contrib as submodule

• Simplify Pypi readme file

• Remove GPU requirement for devcontainer

0.3.0 (2022-02-14)

• Add complete redesign of CLI: main command changed from python -m beobench.experiment.scheduler to beobench run.

• Add support for energym environments

• Add support for MLflow experiment tracking

• Add support for custom agents

0.2.1 (2022-02-03)

• Add integration with sinergym

• Move gym integrations to separate beobench_contrib repo

• Make usage of GPUs in containers optional

0.2.0 (2022-01-18)

• Enable adding custom environments to beobench with docker build context-based syntax

• Save experiment results on host machine

• Major improvements to documentation

• Remove unnecessary wandb arguments in main CLI

0.1.0 (2022-01-10)

• First release on PyPI.