Xland minigrid Burundi
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context
Environment. XLand-MiniGrid is a complete rewrite of MiniGrid (Chevalier-Boisvert et al., 2023) in JAX (Bradbury et al., 2018), incorporating a notion of rules and goals from XLand (Team et al., 2023). Leveraging JAX, it can run on a GPU or TPU accelerators at millions steps per seconds. At its core, it is a goal-oriented
XLand-MiniGrid: Scalable Meta-Reinforcement Learning
We present XLand-Minigrid, a suite of tools and grid-world environments for meta-reinforcement learning research inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid. XLand-Minigrid is written in JAX, designed to be highly scalable, and can potentially run on GPU or TPU accelerators, democratizing large-scale
[Feature Request] Add Maze-like env · Issue #2 · corl-team/xland-minigrid
We''re unfortunately unlikely to be doing this anytime soon (it''s in the plans for post v1.0, ~2-3 months), as we''re currently busy working on getting XLand-MiniGrid to full paper and focused on meta-RL part (benchmarks), but we welcome any contributions, as grid randomization will definitely add new challenges to the meta-learning, as well as
Paper page
XLand-Minigrid is written in JAX, designed to be highly scalable, and can potentially run on GPU or TPU accelerators, democratizing large-scale experimentation with limited resources. To demonstrate the generality of our library, we have implemented some well-known single-task environments as well as new meta-learning environments capable of
[PDF] XLand-MiniGrid: Scalable Meta-Reinforcement Learning
XLand-MiniGrid is a suite of tools and grid-world environments for meta-reinforcement learning research that can potentially run on GPU or TPU accelerators, democratizing large-scale
Российские учёные создали первую открытую среду для
Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learning research. Written in JAX, XLand-MiniGrid is designed to be highly scalable and can potentially run on GP
NeurIPS XLand-MiniGrid: Scalable Meta-Reinforcement Learning
Abstract: We present XLand-Minigrid, a suite of tools and grid-world environments for meta-reinforcement learning research inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid. XLand-Minigrid is written in JAX, designed to be highly scalable, and can potentially run on GPU or TPU accelerators, democratizing large-scale experimentation
Учёные из T-Bank AI Research и AIRI создали
Например, в XLand-MiniGrid собрано 100 млрд примеров действий искусственного интеллекта в 30 тыс. задач. Это позволяет использовать готовые датасеты для обучения, а не проводить его каждый раз с нуля.
XLand-MiniGrid
XLand-MiniGrid is a suite of tools, grid-world environments and benchmarks for meta-reinforcement learning research inspired bynthe diversity and depth of XLandnand the simplicity and minimalism of MiniGrid. Despite the similarities,nXLand-MiniGrid is written in JAX from scratch and designed to be highly scalable, democratizing large-scale
[2312.12044v3] XLand-MiniGrid: Scalable Meta-Reinforcement
Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learning research. Written in JAX, XLand-MiniGrid is designed to be highly scalable and can potentially run on GPU or TPU accelerators, democratizing large-scale
XLand-MiniGrid: Scalable Meta-Reinforcement Learning
Written in JAX, XLand-MiniGrid is designed to be highly scalable and can potentially run on GPU or TPU accelerators, democratizing large-scale experimentation with limited resources. Along with the environments, XLand-MiniGrid provides pre-sampled benchmarks with millions of unique tasks of varying difficulty and easy-to-use baselines that
Abstract
MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environ-ments for meta-reinforcement learning research. Written in JAX, XLand-MiniGrid is designed to be highly scalable and can potentially run on GPU or TPU acceler-ators, democratizing large-scale experimentation with limited resources. Along
Papers with Code
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. dunnolab/xland-minigrid • • 19 Dec 2023. Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learning research.
Alexander Nikulin
Alexander Nikulin. Hi there! I am a PhD student at MIPT, studying Offline Reinforcement Learning.I''m also working as a Senior Research Scientist at AIRI, publishing papers and supervising students fore AIRI, I worked at Tinkoff AI.I''m best known for my work as a core developer of the CORL library and the XLand-MiniGrid environment. Before that, I completed a
xminigrid
XLand-MiniGrid is a suite of tools, grid-world environments and benchmarks for meta-reinforcement learning research inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid. Despite the similarities, XLand-MiniGrid is written in JAX from scratch and designed to be highly scalable, democratizing large-scale
xland-minigrid 开源项目教程
近几年,机器学习的安全问题逐渐被研究者们所重视。其中最热门的方向之一就是人脸对抗攻击。 全球范围内,从社交媒体中的照片标记到自动边境控制 (abc),人脸识别 (fr) 系统展示了出色的验证性能,证明这项技术适用于现实世界。
XLand-MiniGrid: Scalable Meta-Reinforcement Learning
We present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learning research inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid. XLand-Minigrid is written in JAX, designed to be highly scalable, and can potentially run on GPU or TPU accelerators,
XLand-MiniGrid: Scalable Meta-Reinforcement Learning
We present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learning research inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid. XLand-Minigrid is written in JAX, designed to be highly scalable, and can potentially run on GPU or TPU accelerators, democratizing large-scale experimentation with limited
[PDF] XLand-MiniGrid: Scalable Meta-Reinforcement Learning
XLand-MiniGrid is a suite of tools and grid-world environments for meta-reinforcement learning research that can potentially run on GPU or TPU accelerators, democratizing large-scale experimentation with limited resources. Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid
2312.12044
XLand-Minigrid is written in JAX, designed to be highly scalable, and can potentially run on GPU or TPU accelerators, democratizing large-scale experimentation with limited resources. To demonstrate the generality of our library, we have implemented some well-known single-task environments as well as new meta-learning environments capable of
[晓理紫]每日论文分享(有中文摘要,源码或项目地址)--强化学习、机器人等_xland-minigrid
文章浏览阅读813次,点赞16次,收藏13次。受XLand的多样性和深度以及MiniGrid的简单性和极简主义的启发,我们推出了XLand-MiniGrid,这是一套用于元强化学习研究的工具和网格世界环境。XLand-MiniGrid是用JAX编写的,它被设计成高度可扩展的,并且有可能在GPU或TPU加速器上运行,从而在有限的资源下实现大
Abstract arXiv:2312.12044v2 [cs.LG] 6 Feb 2024
Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learn-ing research. Written in JAX, XLand-MiniGrid is designed to be highly scalable and can poten-tially run on GPU or TPU accelerators, democ-
MiniGrid Documentation
Minigrid contains simple and easily configurable grid world environments to conduct Reinforcement Learning research. This library was previously known as gym-minigrid. Toggle site navigation sidebar. MiniGrid Documentation. Farama Foundation Hide navigation sidebar. Hide table of contents sidebar
[2312.12044] XLand-MiniGrid: Scalable Meta-Reinforcement
Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learning research. Written in JAX, XLand-MiniGrid is designed to be highly scalable and can potentially run on GPU or TPU accelerators, democratizing large-scale
[晓理紫]每日论文分享(有中文摘要,源码或项目地址)--强化学习、
We present XLand-100B, a large-scale dataset for in-context reinforcement learning based on the XLand-MiniGrid environment, as a first step to alleviate this problem. It contains complete learning histories for nearly
NeurIPS Poster XLand-MiniGrid: Scalable Meta-Reinforcement
Written in JAX, XLand-MiniGrid is designed to be highly scalable and can potentially run on GPU or TPU accelerators, democratizing large-scale experimentation with limited resources. Along with the environments, XLand-MiniGrid provides pre-sampled benchmarks with millions of unique tasks of varying difficulty and easy-to-use baselines that
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