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.

我们介绍了结构化主动推理，这是使用范畴系统理论的一种大规模推演和形式化主动推理。我们将生成模型形式化地表现为 “在接口上” 的系统，并将接口看作通常的马尔科夫毯的组合抽象；而代理是它们生成模型的 ' 控制器 '，与它们形式上是对偶的。这为主动推理开辟了新的研究领域，例如：具有结构化接口的代理（例如，具有 ' 模式依赖性 ' 或与计算机 API 交互的代理）；可以管理其他代理的代理；以及使用主动推理来更改其（内部或外部）结构的 “元代理”。通过使用结构化接口，我们还获得了结构化（' 类型化 '）策略，这些策略便于形式验证，这是实现安全人工智能代理的重要一步。此外，我们可以利用范畴逻辑将代理的目标描述为形式化的谓词，其满足性可能取决于交互环境。这指向了强大的组合工具，用于限制和控制自组织代理集合。