Seeing DAM in Motion
What a system does over time is what it is.
Why Simulate?
Mathematical models must breathe to be believed.
In DAM, the value of structure lies in its unfolding — its response to time, tension, and transformation.
This page hosts a growing set of simulations that:
- Illustrate core dynamics of the DAM architecture
- Demonstrate how adaptation plays out across layers
- Visualize learning, failure, and evolution in real time
Simulation Categories
1. Single Entity Adaptation
- How does an isolated agent evolve under shifting feedback?
- How do goals (
Hᵢ) and internal time (τᵢ) affect its behavior? - Watch a node learn to re-align or stagnate and reset
Coming modules:
- Error-gradient loops
- Entropy-driven time dilation
- Adaptive goal switching
2. Dynamic Network Evolution
- A network of agents with evolving connection weights (
θᵢⱼ) - Observe how relational tension reorganizes structure
- Includes visualization of:
- Link strengthening and decay
- Emergent subgroups
- Collapse and regeneration cycles
3. Energy-Entropy Coherence Simulation
- Agents operate with limited energy budgets
- Rising entropy disrupts temporal flow
- Goal: maintain local adaptation while minimizing energy burn
Includes:
- Coherence map overlays
- System-wide entropy pressure meters
- Self-correction under energy constraints
4. Meta-Evolution Feedback
- The system rewrites its own rules
- Learning rates, update equations, even network topology can shift
- Introduces self-referential loops and recursive adaptation
Here, the model not only adapts — it adapts how it adapts.
Tools & Visualizations (in development)
We’re building interactive dashboards for:
- Graph evolution (force-directed and dynamic layouts)
- Temporal rhythm tracking (per-entity clocks)
- Energy/entropy overlays
- Strategy shifts & error-reactive graphs
- Meta-evolution logs (version history of rulesets)
Source & Methodology
All simulations will be:
- Open source (via [GitHub])
- Documented with design notes and equations
- Paired with commentary: what to watch, what it means
Built in Python (NumPy, networkx, matplotlib), with eventual web deployment via JS or interactive frameworks like Observable or PyScript.
Connected Concepts
/organism/architecture→ Understand the layers before simulating/interface/observer-logic→ How the model watches itself/atelier→ Build and test your own simulations