概述
pymdp 实现了部分可观测马尔可夫决策过程下的离散状态主动推理,并通过一篇被 PubMed 认-indexed 的步骤详解教程引入社区。它由 infer-actively 组织维护,由 Conor Heins 领导,是研究院计算领域页面和学习材料中引用的基础工具。
此页面由机器翻译成中文。 查看英文原版。
研究人员和开发人员正在使用Python构建或模拟离散状态Active Inference生成性模型。
Python实现的Active Inference,适用于部分可观测马尔可夫决策过程。
在本页
pymdp 是一个用于离散状态(POMDP)主动推理的开源 Python 包,广泛应用于研究社区中用于构建和模拟生成模型。它是外部生态系统实现,不同于研究院自身的项目,研究院引用并围绕其开发学习材料。
pymdp 实现了部分可观测马尔可夫决策过程下的离散状态主动推理,并通过一篇被 PubMed 认-indexed 的步骤详解教程引入社区。它由 infer-actively 组织维护,由 Conor Heins 领导,是研究院计算领域页面和学习材料中引用的基础工具。
贡献、问题和讨论直接在上游的GitHub存储库中发生;研究院的Discord是一个找到在其之上构建的人的好地方。
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