Xland minigrid The Netherlands
[PDF] XLand-MiniGrid: Scalable Meta-Reinforcement
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
[2312.12044] XLand-MiniGrid: Scalable Meta-Reinforcement
Abstract: 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
Abstract
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 environ-ments for meta-reinforcement
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
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
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,旨在实现高度可扩展性,使资源有限的团队也能进行大规模实验。
[2312.12044] XLand-MiniGrid: Scalable Meta-Reinforcement
Abstract: 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
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
Paper page
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
GitHub
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: 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
Abstract
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 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-
[PDF] XLand-MiniGrid: Scalable Meta-Reinforcement
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.
GitHub
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
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-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.
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
[PDF] XLand-MiniGrid: Scalable Meta-Reinforcement
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
5 FAQs about [Xland minigrid The Netherlands]
Is xLand-minigrid scalable?
esearch. Written in JAX, XLand-MiniGrid is designed to be highly scalable and capable of running on GPU or TPU accelerators, and can achieve millions of steps pe second. In addition, we have implemented easy-to-use baselines and provided preliminary analysis of their performance and generalization, showing that the proposed benchmarks are cha
Can xLand-minigrid help practitioners perform meta-reinforcement learning experiments faster?
ck time. While we do not introduce any novel algorithmic improvements in our work, we hope that the proposed highly scalable XLand-MiniGrid environments will help practitioners perform meta-reinforcement learning experiments at scale faster and with fewer r
What is xLand-minigrid environment interface?
Similar to Jumanji (Bonnet et al., 2023), XLand-MiniGrid Environment interface is inspired by the dm_env API (Muldal et al., 2019), which is particularly well suited for the meta-RL, as it separates episodes from trials by design (see Section D.1 ). Thus, each environment should provide jit-compatible reset, reset_trial and step methods.
How many rules can xLand-minigrid use?
Full-scale XLand environment can use more than five rules according to the Team et al. ( 2023). To test XLand-MiniGrid in similar conditions we report simulation throughput varying number of rules. For testing purposes we just replicated same NEAR rule multiple times in the PutNear environment.
Does xLand support multi-agent simulations?
library.Compared to the full-scale XLand (Team et al., 2021, 2023), we do not currently support multi-agent simulations, procedural generation of complex worlds, rules with multiple output entities, or goal com
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