# A Modular Perspective Layer for Active Inference Agents Presenter: Hongju Pae Contribution: Interactive Workshop Public ID: talk-7bfba1b90b06334d ## Submitted abstract Most agent architectures collapse two things that phenomenology keeps apart: what the agent should do immediately, and what kind of world the agent takes itself to be in. This session introduces “perspective” as a distinct architectural layer that carries the second. Perspective is a slowly evolving, history-sensitive latent state that gates how observations are encoded. Importantly, it is decoupled from policy gradients and is never itself an optimization target. Because it is decoupled, it is portable and can be attached on top of an existing policy-optimizing agent rather than requiring a bespoke design. The first part of the session develops the conceptual frame: how a phenomenologically motivated condition translates into a concrete architectural commitment, and why that commitment is orthogonal to belief-state inference and policy selection. I then trace the capabilities that this single layer has been shown to support across a sequence of studies, including directional hysteresis, history-dependent perceptual reorganization, and body-grounded conative orientation, treating these as unified aspects of a single portable module. There will then be a live demonstration attaching the perspective layer to an active inference agent, such as a hierarchical Bayesian / discrete state-space model, and running it in parallel with its unaugmented counterpart in the same environment, so participants can see exactly what the layer adds and where it plugs in. The session closes with a structured discussion in which participants are invited to identify candidate insertion points for a perspective layer in their own active inference agents, whether built in PyMDP, RxInfer, or custom frameworks. The aim is to leave participants able to reason about whether and how a subjective perspective could be added. Source: [submitted source]() Abstract SHA256: 52989bb421dddd9c78c2b4a2d77e98d7e180d842e16e392fbfad17a36a1a7413 ## Organizer review checklist - [ ] Confirm the submitted title, presenter, and abstract with the presenter. - [ ] Confirm contribution format and scheduling needs. - [ ] Confirm public permissions for any additional material before publication. - [ ] Prepare discussion questions grounded in the submitted abstract. ## Public learning resources These approved event resources are starting points; topic relevance and author identity have not been inferred. - Active Inference Ontology: https://github.com/ActiveInferenceInstitute/Active_Inference_Ontology - Cognitive Agent Modeling: https://github.com/ActiveInferenceInstitute/ActiveInferenceImplementations - GEO-INFER: https://github.com/ActiveInferenceInstitute/GEO_INFER - Generalized Notation Notation: https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation - pymdp: https://github.com/infer-actively/pymdp - Reproducible publication template: https://github.com/docxology/template OpenAlex discovery-only search (not a verified identity or literature match): https://openalex.org/works?search=A%20Modular%20Perspective%20Layer%20for%20Active%20Inference%20Agents