Predictive Cuisine: A Closed-Loop Architecture Linking Structured Recipes, Sensory Simulation and Observed Multisensory Outcomes
Year: 2026
Type: peer-review
Abstract: Predictive Cuisine is proposed as a sensory digital prototyping architecture in which a versioned recipe-process object is bound to a provenance-aware simulated multisensory state (MP6-SIM) before physical execution and, after execution, to an observed multisensory state (MP6-OBS) represented under a declared comparison contract — so that prediction error becomes an auditable object rather than an informal comment. The individual ingredients of this architecture — recipe ontologies, food-process modelling, computational sensory prediction, AI-assisted formulation and food digital twins — have substantial prior art [1–9]. The research question is whether their explicit coupling through portable, versioned JRF/MP6 objects enables reproducible sensory prototyping and learning from prediction error. We report the initiating case (Elixir of Invincibility v1.1.0, August 2026): a manually executed end-to-end workflow from social-media recipe extraction through structured repair and versioning, AI-assisted sensory projection, provenance-flagged predicted-profile reconstruction, contextual handoff, and a downstream-LLM process decision. The case demonstrates a systems workflow and surfaces concrete engineering requirements; it demonstrates no predictive accuracy, and none is claimed.
Author: Wayenberg, Francois
Institution: Université Libre de Bruxelles
Language: English
Topic: Culinary Culture and Tourism
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7204193646