结构化主动推理(扩展摘要)

Toby St Clere Smithe
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引用次数: 0

摘要

我们引入了结构化主动推理,它是使用分类系统理论工具对主动推理进行的大规模概括和形式化。我们将生成模型正式视为 "界面 "上的系统,后者是对马尔可夫空白集通常概念的组合抽象;然后,代理是其生成模型的 "控制器",在形式上与生成模型互为独立。这为主动推理开辟了新的前景,例如:具有结构化界面(如 "模式依赖 "或与计算机应用程序接口交互)的代理;可以管理其他代理的代理;以及利用主动推理改变其(内部或外部)结构的 "元代理"。有了结构化接口,我们还可以获得结构化("类型化")策略,这些策略可以进行形式化验证,这是向安全人工代理迈出的重要一步。此外,我们还可以利用分类逻辑将代理的目标描述为形式谓词,其满足与否可能取决于交互环境。这就为我们提供了强大的组合工具,用于约束和控制自组织代理集合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structured Active Inference (Extended Abstract)
We introduce structured active inference, a large generalization and formalization of active inference using the tools of categorical systems theory. We cast generative models formally as systems "on an interface", with the latter being a compositional abstraction of the usual notion of Markov blanket; agents are then 'controllers' for their generative models, formally dual to them. This opens the active inference landscape to new horizons, such as: agents with structured interfaces (e.g. with 'mode-dependence', or that interact with computer APIs); agents that can manage other agents; and 'meta-agents', that use active inference to change their (internal or external) structure. With structured interfaces, we also gain structured ('typed') policies, which are amenable to formal verification, an important step towards safe artificial agents. Moreover, we can make use of categorical logic to describe express agents' goals as formal predicates, whose satisfaction may be dependent on the interaction context. This points towards powerful compositional tools to constrain and control self-organizing ensembles of agents.
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