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v0.0.4
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puyuan1996 committed Feb 21, 2024
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13 changes: 13 additions & 0 deletions CHANGELOG.md
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2024.02.08 (v0.0.4)
- polish: add agent configurations & polish replay video saving method (#184)
- polish: polish comments in worker files
- polish: polish comments in tree search files (#185)
- polish: rename mcts_mode to battle_mode_in_simulation_env, add sampled alphazero config for tictactoe (#179)
- polish: polish redundant data squeeze operations (#177)
- polish: polish the continuous action process in sez model
- polish: polish bipedalwalker env
- fix: fix completed value inf bug when zero exists in action_mask in gumbel muzero (#178)
- fix: fix render settings when using gymnasium (#173)
- fix: fix lstm_hidden_size in sampled_efficientzero_model.py
- fix: fix action_mask in bipedalwalker_cont_disc_env, fix device bug in sampled efficientzero (#168)

2023.12.07 (v0.0.3)
- env: MiniGrid env (#110)
- env: Bsuite env (#110)
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2 changes: 1 addition & 1 deletion README.md
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[![Contributors](https://img.shields.io/github/contributors/opendilab/LightZero)](https://github.com/opendilab/LightZero/graphs/contributors)
[![GitHub license](https://img.shields.io/github/license/opendilab/LightZero)](https://github.com/opendilab/LightZero/blob/master/LICENSE)

Updated on 2023.12.07 LightZero-v0.0.3
Updated on 2024.02.08 LightZero-v0.0.4

> LightZero is a lightweight, efficient, and easy-to-understand open-source algorithm toolkit that combines Monte Carlo Tree Search (MCTS) and Deep Reinforcement Learning (RL).
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2 changes: 1 addition & 1 deletion README.zh.md
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[![Contributors](https://img.shields.io/github/contributors/opendilab/LightZero)](https://github.com/opendilab/LightZero/graphs/contributors)
[![GitHub license](https://img.shields.io/github/license/opendilab/LightZero)](https://github.com/opendilab/LightZero/blob/master/LICENSE)

最近更新于 2023.12.07 LightZero-v0.0.3
最近更新于 2024.02.08 LightZero-v0.0.4

> LightZero 是一个轻量、高效、易懂的 MCTS+RL 开源算法库。
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2 changes: 1 addition & 1 deletion setup.py
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setup(
name='LightZero',
version='0.0.3',
version='0.0.4',
description='A lightweight and efficient MCTS/AlphaZero/MuZero algorithm toolkits.',
long_description_content_type='text/markdown',
author='opendilab',
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