Morocco xland minigrid

[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

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,

[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

XLand-MiniGrid: Scalable Meta-Reinforcement Learning

5 天之前· 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

XLand-MiniGrid：JAX中的元强化学习利器

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规模实验的民主化。

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

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

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

ICML 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

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

XLand-MiniGrid

Продукт XLand-MiniGrid, История, 2024 Анонс продукта. История 2024: Анонс продукта. 29 ноября 2024 года стало известно о том, что российские ученые из лаборатории T-Bank AI Research и Института AIRI в сотрудничестве со студентами МФТИ

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.

NAVIX: Scaling MiniGrid Environments with JAX

XLand-MiniGrid reproduces Minigrid−like observations but focuses on designing a set of compos-able rules that can be used to generate a wide range of environments, rather than reimplementing the original Minigrid suite. To conclude, MiniGrid is a fundamental tool for Deep RL experiments, at the base of a high number

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

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

XLand-100B: первый в мире большой

Назвали ее XLand‑MiniGrid, т.к. она вдохновлена и берет лучшее от XLand от DeepMind и от широко известной в комьюнити минималистичной MiniGrid. Она представляет собой grid‑world с разреженной наградой

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

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.,

[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

XLand-100B: A Large-Scale Multi-Task Dataset for In-Context

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 grid-world environment with simple

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：JAX中的元强化学习利器

XLand-MiniGrid 是一个专为元强化学习研究设计的工具套件,结合了 XLand 的多样性和深度,以及 MiniGrid 的简洁性和极简主义。该项目完全使用 JAX 从头开始构建,旨在

Roadmap to v1.0 · Issue #1 · corl-team/xland-minigrid

Key (like in Minigrid) Door (like in Minigrid) Box (like in Minigrid) (may reduce FPS!!!) Actions. stochasticity (could be done with a wrapper) Rules & Goals. procedural generator (like in xland v2) pre-sampled benchmarks, 500-1M tasks; Map. different grid layouts (mazes, rooms, objects) Envs. porting majority of minigrid envs; full xland

[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

NAVIX: Scaling MiniGrid Environments with JAX

Nikulin et al. proposes XLand-MiniGrid, a suite of grid-world environments for meta RL. Like [Jiang et al., 2023 ], XLand-MiniGrid reproduces Minigrid − - - like observations but focuses on designing a set of composable rules that can be used to generate a wide range of environments, rather than reimplementing the original Minigrid suite.

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