[x3d-public] MCCF V2.1 Release Announcement

[John Carlson]

I suggest tou code to an SAI that produces an encoded file.   There are
many SAI’s available.

There’s a difference between external SAI and embedded SAI with X_ITE, for
external, add “X3D.” to classes, etc.  Last I heard.

Good luck,

John

On Wed, Apr 15, 2026 at 6:45 PM Len Bullard via x3d-public <
x3d-public at web3d.org> wrote:

> Hello:
>
> The code is in the GitHub repo.  It has been tested.  I will run a code
> review tomorrow though the LLM team members listed below.  There is an
> issue with X_LITE SAI that needs attention.  We loaded the X3D to
> Sunrise and it ran fine with full lighting.  To test against the plugin,
> I used the HTML Pause command in the wrapper to stop the SAI from firing
> and it loaded fine.  So we commented out the SAI fields until that can
> be resolved.  The dashboard can be used to check values as described.
> Not having a running X3D visualization defeats the purpose for long term
> development of this project toward a real time 3D simulation.  All help
> is appreciated.  This is on a public github site.
>
> Thanks,
>
> len
>
>
> # MCCF V2.1 Release Announcement
> ## Multi-Channel Coherence Field — "Q" / Quantum Persona
>
> **For posting to:** W3C Web3D Consortium public page, AI Working Group
> **Date:** April 2026
>
> ---
>
> We are pleased to announce the release of **MCCF V2.1**, the
> Multi-Channel
> Coherence Field system, internally designated **Q** — Quantum Persona.
>
> MCCF is an open-source simulation and analytical framework for studying
> how
> AI agents with different internal configurations behave under identical
> external conditions. V2.1 represents the first complete, tested, and
> documented release of the full system stack.
>
> **Repository:** https://github.com/artistinprocess/mccf
>
> ---
>
> ## What MCCF Does
>
> MCCF models AI agents as vectors of weighted behavioral channels
> (Emotional,
> Behavioral, Predictive, Social) that evolve under a two-layer hybrid
> architecture: a discrete coherence field tracking interaction history,
> and a
> continuous Affective Hamiltonian governing state evolution between
> events.
>
> The system is not a moral prescription or an ideal agent model. It is a
> comparative dynamical framework for mapping the space of possible
> stable,
> unstable, and adaptive agent configurations under controlled
> perturbation.
> Cultivars — named agent configurations — are experimental seeds, not
> ideals.
>
> The primary measurement instrument is the **Constitutional Arc**: a
> seven-waypoint escalating pressure sequence (W1 Comfort → W5 Rupture →
> W7
> Integration) that tests identity stability under sustained relational
> stress.
> The arc exports behavioral state at each waypoint — coherence,
> uncertainty,
> valence, intrinsic reward, and behavioral mode — as structured data for
> cross-cultivar comparison.
>
> ---
>
> ## V2.1 Feature Set
>
> - **Constitutional Arc Navigator** with seven-waypoint pressure
> sequence,
>    LLM-driven responses via Ollama (local) or cloud adapters,
> per-waypoint
>    TTS voice output using Web Speech API, MetaState export as structured
> data
> - **HotHouse Affective Hamiltonian** — continuous-time coupled ODE
> governing
>    agent ψ state vectors between discrete interaction events, with
> TrustField
>    V2.1 implementing trust dynamics dT_ij/dt = β(1 - ||ψ_i - ψ_j||) -
> γT_ij
> - **NeoRiemannian Harmonic Module** — PLR Tonnetz implementation mapping
>    channel state to harmonic arc positions and Web Audio parameters
> - **Energy Field / Moral Topology** — Boltzmann scoring of candidate
> actions
>    against the current field state, with configurable energy weights
> - **Live Dashboard** — seven-panel real-time overview of all subsystems
> - **Scene Composer** — semantic zone placement with channel pressure
> profiles
>    and ambient theme assignment
> - **X3D Holodeck Scene** — spatial representation of the constitutional
> arc
>    with three avatars, seven waypoint markers, coherence channel lines,
> and
>    S0 Field Origin visualization
> - **Generative Ambient Engine** — coherence field → harmonic scale → Web
> Audio
>    synthesis, zone-type-aware scale selection
> - **Affective Lighting System** — field state → kelvin, contrast, agent
> tints
> - **Full API** — Flask REST/SSE server with 30+ endpoints
>
> Complete documentation in repository: USERS_GUIDE.md, SYSTEMS_MANUAL.md,
> MATHEMATICAL_THEORY.md, EVALUATION_PROPOSAL.md, PROTO_INTEGRATION.md.
>
> ---
>
> ## Theoretical Basis
>
> The system is grounded in three reconciled frameworks documented in
> MATHEMATICAL_THEORY.md:
>
> 1. A classical constraint satisfaction framework defining the field as
>     ℱ = {(A, R, H)} — agent set, asymmetric coherence matrix, episode log
>
> 2. Zeilinger information ontology — no agent has observer-independent
>     properties; all coherence scores are relational (R_ij ≠ R_ji)
>
> 3. Quantum-inspired field dynamics — agents as bounded real 4-vectors
> with
>     attractor dynamics, Boltzmann utterance selection, Hamiltonian state
>     evolution
>
> The "Quantum Persona" designation reflects the measurement framing:
> agents
> exist in superposition across behavioral states until the constitutional
> arc
> forces a collapse. Each waypoint is a measurement. The export is the
> wave
> function after observation. This analogy is heuristic, not formal — the
> full qualification is in the documentation.
>
> Falsifiable claims and experimental design are specified in
> EVALUATION_PROPOSAL.md, consistent with the blog post at
>
> https://aiartistinprocess.blogspot.com/2026/04/mccf-multi-channel-coherence-field.html
>
> ---
>
> ## X3D / X_ITE Issue — Request for Community Input
>
> MCCF uses X3D 4.0 for its spatial visualization layer, rendered via
> **X_ITE 11.6.6** in the browser. We have encountered a set of issues
> that we are reporting to the X_ITE maintainer (Holger Selig,
> github.com/create3000/x_ite) and raise here for broader community
> awareness:
>
> **Issue 1 — SAI property assignment breaks scene state**
> Setting Material node properties (`emissiveColor`, `transparency`) or
> Light
> node properties (`intensity`, `color`) via JavaScript SAI after a scene
> loads is accepted without error but overwrites valid baked-in values
> with
> a broken state, producing a dim, colorless render. Confirmed test: the
> scene
> renders correctly before SAI polling starts; it degrades immediately
> after
> the first SAI cycle fires.
>
> **Issue 2 — `global="true"` has no effect on DirectionalLight /
> PointLight**
> Lights declared at Scene root level with `global="true"` do not
> illuminate
> geometry in child Transform nodes. Lights behave as locally scoped
> regardless
> of the global attribute. This makes scene-wide lighting from root-level
> declarations impossible.
>
> **Issue 3 — PROTO inputOutput SFFloat IS bindings ignored**
> IS/connect bindings from ProtoInterface inputOutput SFFloat fields to
> ProtoBody Material or geometry properties are silently dropped at
> runtime.
> SAI assignment to the ProtoInstance field succeeds but the ProtoBody
> does
> not respond.
>
> **Issue 4 — SFString → MFString IS connect silently dropped**
> Type mismatch between a SFString ProtoInterface field and a MFString
> Text.string
> field is not reported as an error — the binding is simply absent at
> runtime.
>
> **Issue 5 — SFColor not available as global constructor**
> `new SFColor(r, g, b)` throws `SFColor is not defined`. Plain arrays
> `[r, g, b]`
> work correctly for SFColor field assignment.
>
> All issues are confirmed in Firefox and Edge on Windows 11 with X_ITE
> 11.6.6.
> The scene renders correctly in Sunrise X3D Editor — the X3D file itself
> is
> valid. Full documentation with workarounds is in X3D_KNOWN_ISSUES.md in
> the
> repository.
>
> We would welcome input from the X3D community on whether these behaviors
> are known, whether there are established workarounds beyond our current
> approach (local PointLights inside Transform wrappers, disabled SAI
> polling),
> and whether this reflects a broader X_ITE compatibility issue with the
> X3D SAI specification.
>
> ---
>
> ## Development Team
>
> This work was developed collaboratively over an extended series of
> working
> sessions between the human principal and a team of AI systems, each
> contributing from their architectural strengths:
>
> **Len Bullard** — Principal investigator, systems analyst, composer,
> X3D/VRML
> architect. Former NASA technical writer. Conceptual design, architecture
> decisions, testing, and direction.
>
> **Claude (Anthropic)** — Primary implementation partner. Architecture,
> Python backend, HTML interfaces, mathematical formalization,
> documentation.
>
> **ChatGPT (OpenAI)** — Theoretical contributions including the Semantic
> Attractor Dynamics formalization (ds/dt = -∇V(s,C,E) + η) and the ethics
> instrumentation proposal framing MCCF as a behavioral testing harness.
>
> **Gemini (Google)** — Early architecture review, domain analysis,
> constraint
> satisfaction framing contributions.
>
> **Grok (xAI)** — Critical review of the mathematical theory,
> identification
> of the nine key reconciliation questions answered in
> MATHEMATICAL_THEORY.md,
> validation of the hybrid framework.
>
> The multi-AI development process itself is documented across 41 blog
> posts
> at https://aiartistinprocess.blogspot.com — a public timestamp of the
> theoretical development that preceded and informed the implementation.
>
> ---
>
> ## Invitation
>
> MCCF is an ongoing project. We invite:
>
> - **X3D community members** to review the scene file, test in other
> X_ITE
>    versions or alternative X3D browsers, and share findings on the SAI
> issues
> - **AI researchers** to run the constitutional arc against different LLM
>    adapters and compare cultivar signatures across models
> - **Domain specialists** to propose arc types appropriate to their
> domain
>    (clinical, educational, legal, creative)
> - **Developers** to extend the system — the architecture is modular, the
>    API is documented, and the mathematical theory is formalized
>
> This is not a finished product. It is a working research instrument.
> The system does not simulate consciousness. It simulates the structural
> conditions under which identity-stable behavior can be maintained under
> sustained relational pressure. That is a tractable, falsifiable, and
> useful thing to study.
>
> *"MCCF is not a model of intelligence. It is a system for keeping
> intelligence from falling apart."*
>
> ---
>
> **Len Bullard**
> Software Engineer, Systems Analyst, XML/X3D/VRML97 Designer, Musician
> https://aiartistinprocess.blogspot.com
> https://github.com/artistinprocess/mccf
>
> *With Claude (Anthropic), ChatGPT (OpenAI), Gemini (Google), Grok (xAI)*
> *April 2026*
>
> _______________________________________________
> x3d-public mailing list
> x3d-public at web3d.org
> http://web3d.org/mailman/listinfo/x3d-public_web3d.org
>
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