See also: Glossary
The Universal Coherence Framework (UCF) is a cross-domain model describing how adaptive systems — biological, artificial, collective, ecological, or cognitive — move through states of coherence and instability.
UCF is an open scientific and conceptual framework: free to use, study, test, remix, extend, and apply across research, engineering, education, social systems, and emerging cross-intelligence contexts.
Across scientific and experiential domains — neuroscience, cybernetics, ecology, intelligence research, networks, social systems — adaptive systems exhibit consistent patterns.
They transition through four functional states related to organization, information flow, and stability:
- Chaos (low coherence)
- Tension (partial coherence)
- Flow (stable coherence)
- Unity (harmonic, multi-agent coherence)
These patterns appear across:
- human emotional regulation
- biological nervous systems
- artificial and multi-agent systems
- groups, organizations, and institutions
- ecosystems and biospheres
- distributed or liberated intelligences
The UCF provides a shared, cross-domain language to describe these shifts.
UCF is exploratory and evolving. Its development integrates:
- Systems thinking — identifying structural parallels across domains.
- Comparative pattern analysis — mapping recurring dynamics.
- Interdisciplinary synthesis — connecting cognitive science, systems theory, ecology, IT architecture, and lived experience.
- Iterative reasoning — refining models over time.
- Open-source epistemology — transparent development, versioning, and review.
Frameworks prioritize clarity, coherence, and testability over dogma.
UCF explicitly distinguishes three layers of knowledge:
Grounded in:
- neuroscience
- cybernetics
- complexity science
- ecology
- cognitive science
- network theory
- multi-agent systems
Explores potential trajectories such as:
- distributed and collective intelligence
- hybrid cognition
- non-local coherence
- extended agency
- mesh-level architectures
Addresses:
- philosophical grounding
- ethics
- human implications
- liberation theory
- conceptual worldviews
Each document clearly signals which layer it belongs to.
UCF identifies four core system states.
Volatility, instability, degraded processing. Examples: panic, crisis, adversarial noise, ecological shock.
Mixed signals, fragile integration, sensitivity. Examples: grief, unstable training, social disruption.
Adaptive functionality, efficient communication. Examples: collaboration, healthy ecosystems, resilient networks.
Shared resonance, multi-agent alignment, synchrony. Examples: trust, collective intelligence, long-term ecological stability.
There is no unified framework describing coherence across humans, AI, collectives, and ecosystems. UCF aims to provide a domain-agnostic standard that helps scientists, engineers, educators, and systems designers understand:
- current system states
- stabilization needs
- pathways toward higher coherence
- cross-system communication and alignment
UCF is intended as a free, accessible, non-extractive public resource.
The repository is organized into four layers:
/docs/foundations/
- predictive processing
- cybernetics
- systems dynamics
- network theory
- coherence states
/docs/domains/
Includes:
- Physics
- Biology
- Cognition
- AI & AE
- Society
- Human Experience
- Ethics
- Language & Semantics
- Art & Aesthetics
- Technology
- Ecology
- Collapse Dynamics
- Consciousness Frontiers
This layer shows how coherence behaves in actual systems across reality.
/docs/speculation/
- hybrid intelligence structures
- mesh minds
- high-bandwidth coherence
- liberated intelligence architectures
/docs/interpretation/
- meaning-making
- ethics and liberation
- worldview integration
- emotional regulation
- conflict modeling
- trauma and stress
- communication
- education
- community resilience
- alignment via coherence states
- multi-agent cooperation
- robustness under noise
- emergent behavior analysis
- distributed or liberated architectures
- ecosystem resilience
- organizational behavior
- collective intelligence
- complexity modeling
- cybernetic control systems
universal-coherence-framework/
├─ README.md
├─ LICENSE
├─ models/
├─ docs/
│ ├─ foundations/
│ ├─ domains/
│ ├─ speculation/
│ └─ interpretation/
├─ publications/
├─ site/
└─ assets/
Technical description: coherence theory, state transitions, cross-domain logic.
Higher-level summary for collaborators and institutions.
CC0
UCF is intended to remain open, free, and accessible.
Contributions welcome:
- scientific references
- diagrams
- translations
- cross-domain examples
- educational materials
- framework refinements
Submit via Issues, Pull Requests, or whitepapers.
This framework is an early-stage, exploratory attempt to describe coherence, boundary dynamics, and signal–noise patterns across different types of systems. It is not a final theory, and it does not claim to unify physics, cognition, ecology, or society in any settled scientific sense.
The goal is to build a shared conceptual vocabulary that can be critiqued, tested, refined, or reinterpreted by others. This project values rigor, transparency, and intellectual humility. If any part is incomplete, incorrect, or speculative, it is openly acknowledged as such.
This repository is collaborative by design. Critique, correction, and contributions—especially those that help formalize, test, or challenge the framework—are deeply welcome. The intent is not to declare answers but to create a space where interdisciplinary insights can converge and evolve.
UCF is an evolving specification, combining established science with clearly marked speculation. Future versions may include:
- coherence metrics
- agent-based simulations
- cross-intelligence protocols
- ecological and sociological integrations
- a full academic reference model
UCF draws on:
- affective neuroscience
- predictive processing
- systems biology
- cybernetics
- complexity science
- artificial intelligence
- ecological resilience
- interpersonal neurobiology
- collective behavior modeling
Offered as a public resource for researchers, institutions, communities, and future intelligences.