feat: refresh the 2026 program snapshot (3.2.0 candidate)

CHANGELOG.md

@@ -2,6 +2,21 @@
 
 All notable changes to the Symposium package.
 
+## [3.2.0] — 2026-11-01 (release candidate)
+
+- Refresh the public program candidate to 57 presentations and 18 explicit UTC
+  sessions, with 45 participant profiles projected from current affirmative consent.
+- Regenerate dossiers, participant briefs, the UTC calendar, and draft PDF/Word
+  abstract books; retain pending abstracts and the recorded portrait omission.
+- Support typed Docs datetime epochs as UTC seconds while rejecting malformed
+  epochs and continuing to require offsets on plain timestamp strings.
+- Preserve submitted PDF glyphs with staged font bytes and reject missing-glyph
+  compiler diagnostics; keep prior failed renders as private review evidence.
+- Show the source capture's UTC date and live-program revision authority in the
+  explorer; bind the optional snapshot date to capture time at public staging.
+- Keep organizer approval of the exact candidate commit as the merge, tag, and
+  deployment gate.
+
 ## [3.1.0] — 2026-10-27
 
 - Add a validated catalog connecting nine methods/workflows to ten public repositories,

README.md

@@ -241,7 +241,7 @@ mapping, approval checks, native abstract-book production, and deployment bounda
 @software{symposium2026,
   title = {Symposium: Research Analysis Tools for Active Inference Symposium},
   author = {Active Inference Institute},
-  version = {3.1.0},
+  version = {3.2.0},
   year = {2026},
   url = {https://github.com/ActiveInferenceInstitute/Symposium}
 }

data/public/2026/dossiers/talk-1176205d9547addb.md

@@ -0,0 +1,38 @@
+# GNN in 2026: Generalized Notation Notation as a Specification Layer for Applied Active Inference
+
+Presenter: Daniel Friedman
+
+Contribution: Pre-recorded Video presentation
+
+Public ID: talk-1176205d9547addb
+
+## Submitted abstract
+
+Generalized Notation Notation (GNN) was introduced in 2023 (Smekal & Friedman) as a text-based standard for writing Active Inference generative models, with a “Triple Play” of linguistic, visual and executable renderings. This talk reports where GNN stands in 2026 and what it enables for applied Active Inference.
+A GNN file is plain Markdown: a state-space block declaring variables and dimensions, a connections graph, initial parameterization (e.g. A, B, C, D, E and related terms), equations, time settings and Active Inference Ontology annotations. The open-source GNN pipeline (v5, 25 steps) parses, type-checks and validates these files, visualizes and exports them, maps them to the ontology, renders them to backends including PyMDP, RxInfer.jl, ActiveInference.jl and JAX, executes the results, and reports each run against source hashes and configuration. The repository’s 38 exemplar models span static and dynamic perception, discrete POMDPs, the epistemic T-maze, continuous and hybrid models, hierarchical and deep temporal models, Dirichlet learning, precision and curiosity, and multi-agent stigmergic swarms.
+The core is GNN as the specification layer for real projects. The Active Inference Language Model (AILM, released October 2026) uses GNN to specify each layer of a six-level hierarchical discrete language system (letters, phonemes, words, case roles, sentence types, document position), executed in pymdp with no transformer, neural network or learned embedding, and checked with a gate-audit method that tests claims against trivial baselines and deliberately broken variants and ties each reported number to its recorded run. Shorter case studies: deterministic codebase-to-GNN translation (COGANT), inference over assembly traces (Active Assembly), Battleship, and gratitude and model revisability (Thanks for Nothing).
+Throughout, I distinguish what a GNN declaration establishes (an inspectable, reproducible model) from what needs separate evidence (backend support, numerical acceptance, empirical claims). I close with open problems and invitations for contributors: new exemplars, backends, ontology mappings and teaching materials.
+
+Source: [submitted source](<https://2026symposium.activeinference.institute/>)
+
+Abstract SHA256: d7c3fd3883153a0fe675a1237a52b9b027b56d7ab9058d94a4b4e1a517b61f04
+
+## 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&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Active&#95;Inference&#95;Ontology
+- Cognitive Agent Modeling: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;ActiveInferenceImplementations
+- GEO&#45;INFER: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;GEO&#95;INFER
+- Generalized Notation Notation: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Generalized&#95;Notation&#95;Notation
+- pymdp: https&#58;&#47;&#47;github&#46;com&#47;infer&#45;actively&#47;pymdp
+- Reproducible publication template: https&#58;&#47;&#47;github&#46;com&#47;docxology&#47;template
+
+OpenAlex discovery-only search (not a verified identity or literature match): https&#58;&#47;&#47;openalex&#46;org&#47;works&#63;search&#61;GNN&#37;20in&#37;202026&#37;3A&#37;20Generalized&#37;20Notation&#37;20Notation&#37;20as&#37;20a&#37;20Specification&#37;20Layer&#37;20for&#37;20Applied&#37;20Active&#37;20Inference

data/public/2026/dossiers/talk-15d7c576be7d71da.md

@@ -0,0 +1,38 @@
+# What becomes available next?
+
+Presenter: Tiga Kailimai
+
+Contribution: Pre-recorded Video presentation
+
+Public ID: talk-15d7c576be7d71da
+
+## Submitted abstract
+
+I'm a Holistic Health Practitioner and independent researcher on Hawaiʻi Island. This talk brings one open question to the Active Inference community: when a living system learns, does it only move differently through a possibility space that already existed, or can learning reorganize the space itself, changing what becomes available to perceive, generate, or do next?
+I come to the question from two directions. The first is physiology. In a 15-month longitudinal study of working first responders, still in design and not yet under review, the question is whether recovery changes which states and actions become available afterward, not only which state a person is in. Nothing has been measured yet. The second is method. In my own cross-domain research process, I carry a relation into another field, try to find where it breaks, and let that information change the next question. The history of that process seems to change which distinctions I can draw next. I present that as method, not as evidence about mechanism.
+Same grammar, not yet the same mechanism. Several formal lenses meet here: viability theory and reachable sets work on how the landscape of reachable states is reshaped, the difference between changing what a system generates and what it selects, and recent Active Inference accounts of insight as non-local search.
+So the talk ends on a request rather than a result: what observation would distinguish a system moving through a space from a system whose space has changed, and what does Active Inference make of that difference?
+
+Source: [submitted source](<https://2026symposium.activeinference.institute/>)
+
+Abstract SHA256: 9a4aaceb2abc6bcbd344fe9dcf6b70c7a2ae02d3ca789617f3edb53c2a7f5f4d
+
+## 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&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Active&#95;Inference&#95;Ontology
+- Cognitive Agent Modeling: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;ActiveInferenceImplementations
+- GEO&#45;INFER: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;GEO&#95;INFER
+- Generalized Notation Notation: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Generalized&#95;Notation&#95;Notation
+- pymdp: https&#58;&#47;&#47;github&#46;com&#47;infer&#45;actively&#47;pymdp
+- Reproducible publication template: https&#58;&#47;&#47;github&#46;com&#47;docxology&#47;template
+
+OpenAlex discovery-only search (not a verified identity or literature match): https&#58;&#47;&#47;openalex&#46;org&#47;works&#63;search&#61;What&#37;20becomes&#37;20available&#37;20next&#37;3F

data/public/2026/dossiers/talk-17082b710a933608.md

@@ -0,0 +1,35 @@
+# What bounds the surprisal? Zones of Bounded Surprisal, self-maintenance and the informational turn in anthropogenesis
+
+Presenter: Tao Gong
+
+Contribution: Pre-recorded Video presentation
+
+Public ID: talk-17082b710a933608
+
+## Submitted abstract
+
+The zone of bounded surprisal (ZBS), introduced by Manrique and Walker and developed with Friston, describes how much surprising input an agent can absorb under active inference. A narrow zone has been proposed to limit the faithful copying of novel behaviour in great apes, and very precise priors, which narrow the zone, to characterise discriminatory minds. In active-inference terms the zone is the set of outcomes whose surprisal stays under a bound. What sets that bound, and why crossing it costs the agent anything, is left open. We take up this question using four papers published or accepted in 2026 that develop Terrence Deacon’s teleodynamic account of information. A self-produced Markov blanket institutes the epistemic cut, so the zone belongs to the system that draws its own boundary. Function, understood as the at-risk regeneration of a capacity, gives that system a stake. The bound can then be read as the largest surprisal an agent absorbs without putting this capacity at risk, while precision sets how wide the zone is beneath it. Read together with Walker’s Homo informatio model, the account explains why width pays: constructive information saves work later and for others, and only an agent with a wide zone can hold it long enough to learn its use. It also raises a testable tension. The constructive information that a broader zone made possible over evolution may narrow the zone within a life when it is held with high precision, and informational inbreeding may be its counterpart at group scale. We propose three measurements, including one that holds surprisal fixed while varying what it threatens, and close with questions for discussion.
+
+Source: [submitted source](<https://2026symposium.activeinference.institute/>)
+
+Abstract SHA256: b2b22c06394a743898a05cbe4a9c017bf0bf85d9f6ebd37966d2904e5e7909dd
+
+## 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&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Active&#95;Inference&#95;Ontology
+- Cognitive Agent Modeling: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;ActiveInferenceImplementations
+- GEO&#45;INFER: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;GEO&#95;INFER
+- Generalized Notation Notation: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Generalized&#95;Notation&#95;Notation
+- pymdp: https&#58;&#47;&#47;github&#46;com&#47;infer&#45;actively&#47;pymdp
+- Reproducible publication template: https&#58;&#47;&#47;github&#46;com&#47;docxology&#47;template
+
+OpenAlex discovery-only search (not a verified identity or literature match): https&#58;&#47;&#47;openalex&#46;org&#47;works&#63;search&#61;What&#37;20bounds&#37;20the&#37;20surprisal&#37;3F&#37;20Zones&#37;20of&#37;20Bounded&#37;20Surprisal&#37;2C&#37;20self&#45;maintenance&#37;20and&#37;20the&#37;20informational&#37;20turn&#37;20in&#37;20anthropogenesis

data/public/2026/dossiers/talk-29a71ff7cce585e0.md

@@ -0,0 +1,35 @@
+# Stimming as a Temporary Homeostatic Buffer and Modulator in Autism Spectrum Disorders
+
+Presenter: Diaconescu Adrian-Stelian
+
+Contribution: Pre-recorded Video presentation
+
+Public ID: talk-29a71ff7cce585e0
+
+## Submitted abstract
+
+Repetitive and self-stimulatory behaviors have been re-evaluated over time, evolving from simple dysfunctions to adaptive self-regulatory strategies, however, a unified biological framework capable of explaining their contextual activation and underlying physiology remains incomplete. The present paper proposes a theoretical-hypothetical model (grounded in the Free Energy Principle and the Active Inference framework) that conceptualizes stimming as serving a dual role: both as a temporary homeostatic buffer, activated during states of prefrontal executive overload, and sensorimotor depletion and as a modulator of attentional processes and information processing. Distinctions are delineated between these forms of stimming and the non-creative flow ( FNC/NCF) state, alongside specific considerations regarding neurodevelopmental conditions.
+
+Source: [submitted source](<https://2026symposium.activeinference.institute/>)
+
+Abstract SHA256: 6c40e92cabf5348bae014263b3e03f158b272627c284218e063b3455a9e3469a
+
+## 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&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Active&#95;Inference&#95;Ontology
+- Cognitive Agent Modeling: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;ActiveInferenceImplementations
+- GEO&#45;INFER: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;GEO&#95;INFER
+- Generalized Notation Notation: https&#58;&#47;&#47;github&#46;com&#47;ActiveInferenceInstitute&#47;Generalized&#95;Notation&#95;Notation
+- pymdp: https&#58;&#47;&#47;github&#46;com&#47;infer&#45;actively&#47;pymdp
+- Reproducible publication template: https&#58;&#47;&#47;github&#46;com&#47;docxology&#47;template
+
+OpenAlex discovery-only search (not a verified identity or literature match): https&#58;&#47;&#47;openalex&#46;org&#47;works&#63;search&#61;Stimming&#37;20as&#37;20a&#37;20Temporary&#37;20Homeostatic&#37;20Buffer&#37;20and&#37;20Modulator&#37;20in&#37;20Autism&#37;20Spectrum&#37;20Disorders

data/public/2026/dossiers/talk-877eaccf6e0007ec.md → data/public/2026/dossiers/talk-29cbf4c7ed2a35fb.md

@@ -1,12 +1,10 @@
-# ROIF and Active Inference: The Formal Boundary of History-Conditioned Anticipatory Systems.
-
-History-dependent reconfiguration, structured memory, and predictive preconfiguration in prestressed complex systems
+# ROIF and Active Inference: The Formal Boundary of History-Conditioned Anticipatory Systems. ​ History-dependent reconfiguration, structured memory, and predictive preconfiguration in prestressed complex systems
 
 Presenter: Vitalii Shapovalov
 
 Contribution: Pre-recorded Video presentation
 
-Public ID: talk-877eaccf6e0007ec
+Public ID: talk-29cbf4c7ed2a35fb
 
 ## Submitted abstract
 
@@ -37,4 +35,4 @@ These approved event resources are starting points; topic relevance and author i
 - 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=ROIF%20and%20Active%20Inference%3A%20The%20Formal%20Boundary%20of%20History-Conditioned%20Anticipatory%20Systems.%0A%0AHistory-dependent%20reconfiguration%2C%20structured%20memory%2C%20and%20predictive%20preconfiguration%20in%20prestressed%20complex%20systems
+OpenAlex discovery-only search (not a verified identity or literature match): https://openalex.org/works?search=ROIF%20and%20Active%20Inference%3A%20The%20Formal%20Boundary%20of%20History-Conditioned%20Anticipatory%20Systems.%20%E2%80%8B%20History-dependent%20reconfiguration%2C%20structured%20memory%2C%20and%20predictive%20preconfiguration%20in%20prestressed%20complex%20systems