Dynamic Adjacency Architecture Model (DAAM)

Dynamic Adjacency Architecture Model (DAAM) is a general framework for modelling systems whose possibility spaces evolve over time. Unlike classical Markov models or fixed‑structure dynamical systems, DAAM treats the adjacency structure itself as a dynamic, updateable object. This allows the model to capture systems that reshape their own pathways, basins, and behaviours as they operate.

The trilogy of papers included here introduces DAAM from first principles, and explores its implications.

1. DAAM Geometry – Architecture of Possibility Spaces (Part 1) Introduces the geometric foundations of DAAM. This paper defines the core structural elements of the model: states, adjacencies, weights, adjacency categories, and the three key structural metrics (volume, diversity, density). It presents DAAM as an architectural framework for representing possibility spaces and the geometry that governs how systems move through them.

2. DAAM Dynamics – Update Operators and Evolving Systems (Part 2) Develops the dynamic layer of the model. This paper introduces the update operator, probability flow, entropy, basin formation, dynamic constraint (attention), and recursive self‑modelling. It formalises how DAAM systems evolve over time, how adjacencies strengthen or weaken, and how the landscape reshapes itself as the system moves through it.

3. Dynamic Adjacency Architecture Model – Applied Paper Explores applications and implications of the model. This paper shows how DAAM can be applied to cognitive processes, adaptive behaviour, ecological systems, technological evolution, and other domains where the space of possibilities is not fixed. It demonstrates how high‑order integration, internal simulation, and complex behaviour emerge naturally from the architecture.

Together, these papers outline a unified approach to modelling systems that are not merely in a landscape, but actively shape the landscape they inhabit. DAAM provides a flexible, general architecture for understanding evolving structures, adaptive behaviour, and the geometry of possibility itself.