From b4ab08a91ddfff1ab9d8a08c1eaf3ae934265d41 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Thu, 27 Jun 2024 14:56:25 +0800 Subject: [PATCH] v0.5.2 --- CHANGELOG | 22 ++++++++++++++++++++++ README.md | 22 +++++++++++++++------- conda/meta.yaml | 2 +- ding/__init__.py | 2 +- 4 files changed, 39 insertions(+), 9 deletions(-) diff --git a/CHANGELOG b/CHANGELOG index 874b0bc616..445d6058f7 100644 --- a/CHANGELOG +++ b/CHANGELOG @@ -1,3 +1,25 @@ +2024.06.27(v0.5.2) +- env: add taxi env (#799) (#807) +- env: add ising model env (#782) +- env: add new Flozen Lake env (#781) +- env: optimize ppo continuous config in MuJoCo (#801) +- env: fix masac smac config multi_agent=True bug (#791) +- env: update/speed up pendulum ppo +- algo: fix gtrxl compatibility bug (#796) +- algo: fix complex obs demo for ppo pipeline (#786) +- algo: add naive PWIL demo +- algo: fix marl nstep td compatibility bug +- feature: add GPU utils (#788) +- feature: add deprecated function decorator (#778) +- style: relax flask requirement (#811) +- style: add new badge (hellogithub) in readme (#805) +- style: update discord link and badge in readme (#795) +- style: fix typo in config.py (#776) +- style: polish rl_utils api docs +- style: add constraint about numpy<2 +- style: polish macos platform test version to 12 +- style: polish ci python version + 2024.02.04(v0.5.1) - env: add MADDPG pettingzoo example (#774) - env: polish NGU Atari configs (#767) diff --git a/README.md b/README.md index cbf9b9d007..b7b3cd76fd 100644 --- a/README.md +++ b/README.md @@ -42,7 +42,7 @@
-Updated on 2024.02.04 DI-engine-v0.5.1 +Updated on 2024.06.27 DI-engine-v0.5.2 ## Introduction to DI-engine @@ -56,10 +56,13 @@ It provides **python-first** and **asynchronous-native** task and middleware abs - Multi-agent RL algorithms: such as QMIX, WQMIX, MAPPO, HAPPO, ACE - Imitation learning algorithms (BC/IRL/GAIL): such as GAIL, SQIL, Guided Cost Learning, Implicit BC - Offline RL algorithms: BCQ, CQL, TD3BC, Decision Transformer, EDAC, Diffuser, Decision Diffuser, SO2 -- Model-based RL algorithms: SVG, STEVE, MBPO, DDPPO, DreamerV3, MuZero +- Model-based RL algorithms: SVG, STEVE, MBPO, DDPPO, DreamerV3 - Exploration algorithms: HER, RND, ICM, NGU -- LLM + RL Algorithms: PPO-max, DPO, MODPO，PromptPG +- LLM + RL Algorithms: PPO-max, DPO, PromptPG - Other algorithms: such as PER, PLR, PCGrad +- MCTS + RL algorithms: AlphaZero, MuZero, please refer to [LightZero](https://github.com/opendilab/LightZero) +- Generative Model + RL algorithms: Diffusion-QL, QGPO, SRPO, please refer to [GenerativeRL](https://github.com/opendilab/GenerativeRL) + **DI-engine** aims to **standardize different Decision Intelligence environments and applications**, supporting both academic research and prototype applications. Various training pipelines and customized decision AI applications are also supported: @@ -72,6 +75,7 @@ It provides **python-first** and **asynchronous-native** task and middleware abs - [PPOxFamily](https://github.com/opendilab/PPOxFamily): PPO x Family DRL Tutorial Course - Real world decision AI applications - [DI-star](https://github.com/opendilab/DI-star): Decision AI in StarCraftII + - [PsyDI](https://github.com/opendilab/PsyDI): Towards a Multi-Modal and Interactive Chatbot for Psychological Assessments - [DI-drive](https://github.com/opendilab/DI-drive): Auto-driving platform - [DI-sheep](https://github.com/opendilab/DI-sheep): Decision AI in 3 Tiles Game - [DI-smartcross](https://github.com/opendilab/DI-smartcross): Decision AI in Traffic Light Control @@ -84,7 +88,10 @@ It provides **python-first** and **asynchronous-native** task and middleware abs - [DOS](https://github.com/opendilab/DOS): [CVPR 2023] ReasonNet: End-to-End Driving with Temporal and Global Reasoning - [LightZero](https://github.com/opendilab/LightZero): [NeurIPS 2023 Spotlight] A lightweight and efficient MCTS/AlphaZero/MuZero algorithm toolkit - [SO2](https://github.com/opendilab/SO2): [AAAI 2024] A Perspective of Q-value Estimation on Offline-to-Online Reinforcement Learning - - [LMDrive](https://github.com/opendilab/LMDrive): LMDrive: Closed-Loop End-to-End Driving with Large Language Models + - [LMDrive](https://github.com/opendilab/LMDrive): [CVPR 2024] LMDrive: Closed-Loop End-to-End Driving with Large Language Models + - [SmartRefine](https://github.com/opendilab/SmartRefine): [CVPR 2024] SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction + - [ReZero](https://github.com/opendilab/LightZero): Boosting MCTS-based Algorithms by Backward-view and Entire-buffer Reanalyze + - [UniZero](https://github.com/opendilab/LightZero): Generalized and Efficient Planning with Scalable Latent World Models - Docs and Tutorials - [DI-engine-docs](https://github.com/opendilab/DI-engine-docs): Tutorials, best practice and the API reference. - [awesome-model-based-RL](https://github.com/opendilab/awesome-model-based-RL): A curated list of awesome Model-Based RL resources @@ -92,8 +99,9 @@ It provides **python-first** and **asynchronous-native** task and middleware abs - [awesome-decision-transformer](https://github.com/opendilab/awesome-decision-transformer): A curated list of Decision Transformer resources - [awesome-RLHF](https://github.com/opendilab/awesome-RLHF): A curated list of reinforcement learning with human feedback resources - [awesome-multi-modal-reinforcement-learning](https://github.com/opendilab/awesome-multi-modal-reinforcement-learning): A curated list of Multi-Modal Reinforcement Learning resources - - [awesome-AI-based-protein-design](https://github.com/opendilab/awesome-AI-based-protein-design): a collection of research papers for AI-based protein design - [awesome-diffusion-model-in-rl](https://github.com/opendilab/awesome-diffusion-model-in-rl): A curated list of Diffusion Model in RL resources + - [awesome-ui-agents](https://github.com/opendilab/awesome-ui-agents): A curated list of of awesome UI agents resources, encompassing Web, App, OS, and beyond + - [awesome-AI-based-protein-design](https://github.com/opendilab/awesome-AI-based-protein-design): a collection of research papers for AI-based protein design - [awesome-end-to-end-autonomous-driving](https://github.com/opendilab/awesome-end-to-end-autonomous-driving): A curated list of awesome End-to-End Autonomous Driving resources - [awesome-driving-behavior-prediction](https://github.com/opendilab/awesome-driving-behavior-prediction): A collection of research papers for Driving Behavior Prediction @@ -482,8 +490,8 @@ We appreciate all the feedbacks and contributions to improve DI-engine, both alg ```latex @misc{ding, - title={DI-engine: OpenDILab Decision Intelligence Engine}, - author={OpenDILab Contributors}, + title={DI-engine: A Universal AI System/Engine for Decision Intelligence}, + author={Yazhe Niu, Jingxin Xu, Yuan Pu, Yunpeng Nie, Jinouwen Zhang, Shuai Hu, Liangxuan Zhao, Ming Zhang, Yu Liu}, publisher={GitHub}, howpublished={\url{https://github.com/opendilab/DI-engine}}, year={2021}, diff --git a/conda/meta.yaml b/conda/meta.yaml index eec460a253..bac8a2c438 100644 --- a/conda/meta.yaml +++ b/conda/meta.yaml @@ -1,7 +1,7 @@ {% set data = load_setup_py_data() %} package: name: di-engine - version: v0.5.1 + version: v0.5.2 source: path: .. diff --git a/ding/__init__.py b/ding/__init__.py index 39161c970a..ce20b05cd7 100644 --- a/ding/__init__.py +++ b/ding/__init__.py @@ -1,7 +1,7 @@ import os __TITLE__ = 'DI-engine' -__VERSION__ = 'v0.5.1' +__VERSION__ = 'v0.5.2' __DESCRIPTION__ = 'Decision AI Engine' __AUTHOR__ = "OpenDILab Contributors" __AUTHOR_EMAIL__ = "opendilab@pjlab.org.cn"