An AI Artist in Process

  From Neuroscience to Narrative: Modeling Emotion Without Feeling It How affective neuroscience, large language models, and MCCF can work together to produce emotionally coherent narrative performances See:  https://aiartistinprocess.blogspot.com/2026/10/mccf-v6-design-specification-event.html Introduction One recurring criticism of the Multi-Channel Coherence Field (MCCF) project is that it provides no evidence that an LLM actually experiences emotions. That criticism is correct, but it addresses an objective the project does not have. MCCF is not an attempt to manufacture artificial consciousness or demonstrate that language models possess subjective emotional experiences. It is an experimental environment for modeling defensible emotional relationships and using those models to shape narrative performance. There is an important distinction between experiencing an emotion and being able to recognize, evaluate, represent, and respond appropriately to emotional information. ...

Watch the MCCF demo A short video of the Multi-Channel Coherence Field working in an X3D scene. Watch it on YouTube . A pleasant surprise, and an important milestone On November 9, 2026, I received an unexpected and particularly welcome report from Paul Garrett Hugel, who had independently downloaded and investigated the Multi-Channel Coherence Field (MCCF) repository. Paul's work is important for several reasons. He did not simply review the documentation or run a prepared demonstration. He established an independent development environment, used a different LLM provider, connected multiple MCCF interfaces, created a narrative scene, and exercised the existing relational couplers. Someone else ran it. What an independent test found, and where V6 goes. Over the weekend Paul Garrett Hugel posted a report to the Web3D AI list about an independent exploration of MCCF. I did not know it was coming. It is the first time someone outside the project has taken the repo...

Watch the MCCF demo A short video of the Multi-Channel Coherence Field working in an X3D scene. Watch it on YouTube . 7 November 2026. How MCCF borrows from S1000D, where it shows up in our files, and why it helps both the people and the language model that work on the documentation. MCCF is a system for building X3D scenes where characters have emotional state, music follows the scene, and an AI can take a part beside the humans. That is a lot of moving parts. The documentation has to keep pace with software that changes every week, and it has to be usable by a person at a keyboard and by a language model that reads, drafts and checks it. We solved that the way the aircraft and defence industries solved it for much bigger machines: we borrowed from S1000D , the international specification for technical publications. The idea in one line: write small pieces, give each piece an address that never changes, and let everything else point at the address. 1. What S1000D...

Watch the MCCF demo A short video of the Multi-Channel Coherence Field working in an X3D scene. Watch it on YouTube . The Ambient Engine turns the emotional state of a scene into music. As the characters' Emotion, Behavior, Predictive and Social values move, the engine changes the scale, the layers of sound and the tempo. It can sound through the browser or through a MIDI device, so a real synthesiser or a digital audio workstation can play it. The same page also holds a small composing workshop that builds a piece from a theme in a MIDI file. It runs as its own page and inside the Scene Composer, in the Ambient tab, and it needs the MCCF server. The idea in one line: the music is not laid over the scene. It reads the same field the characters live in. 1. Three modes The Engine selector chooses how sound is made. Generative builds music live from four layers, steered by the field. MIDI Theme Player plays a MIDI file and lets the field shape how it is played. Theme Wo...

Watch the MCCF demo A short video of the Multi-Channel Coherence Field working in an X3D scene. Watch it on YouTube .   MCCF V6: Narrative Exploration, Comparative Dramaturgy, and Compositional Learning 1. Introduction The MCCF V6 Design Specification establishes an event-oriented architecture for observing, reconstructing, and analyzing narrative behavior over time. The existing MCCF engine provides Emotional, Behavioral, Predictive, and Social (EBPS) dynamics, a network topology for character relationships, and a mechanism for expressing character behavior through narrative events. V6 extends the ability to inspect these dynamics through event clusters, transition provenance, timelines, replay, and diagnostic projections. These capabilities suggest several applications beyond narrative composition. MCCF can serve as an experimental environment in which authors, students, and researchers investigate how narrative structures produce character behavior, how relationships e...

Watch the MCCF demo A short video of the Multi-Channel Coherence Field working in an X3D scene. Watch it on YouTube . MCCF V6 Design Specification: Event Clusters and EBPS Traceability Associates semantically related events across modalities, preserves their causal relationships, and makes the evolution of EBPS state inspectable over narrative time, without adding a second source of truth. Status Draft specification for review (revision 2) Date 30 October 2026 Basis Working proposal of 30 October 2026, revised against the V5 implementation and a reviewer's reading of Agent.observe() Posture Additive. V5 EBPS dynamics are unchanged and remain authoritative Primary users Authors, integrators, diagnosticians, researchers Primary concern Observability and provenance Record the event once. Associate its manifestations. Record the EBPS transition with provenance. Derive the timeline, the dashboard overlays, replay and diagnostics from that shared history. What this ...