CS 6795 · Cognitive Science · Georgia Tech
Cognitive Emergence Simulation
Investigating how coherent collective behavior emerges from populations of boundedly rational agents interacting through small-world networks — using empirical human decision data as a cognitive substrate.
Key Findings
Tipping Ridges
Small increases in communicator presence produce sharp, large-scale shifts in coherence — a clear phase transition boundary in parameter space.
Democratic Resilience
Democratic population archetypes achieved stable coherence at lower communication loads than polarized or hyperconnected environments.
Oscillatory Dynamics
All metrics cycled with a ~1,000-round period before converging — a collective exploration-exploitation phase preceding consensus.
Oracle Anchoring
Populations with at least 75% oracle agents achieved near-perfect coherence across all connectivities. As heuristic dominance increased, coherence dropped sharply.
Hyperconnection Paradox
Very dense networks can reduce coherence — simple update rules amplify noise rather than attenuate it when social saturation is reached.
Listen Ratio Dominates
Responsiveness to communication (listen ratio) had a stronger influence on tipping thresholds than network rewiring probability or topology randomness.
Selected Figures
Figure 1
Time series of entropy, Gini, oracle alignment, and coherence across 5,000 timesteps. Oscillations with ~1,000-round period precede convergence.
Figure 2
Watts-Strogatz small-world topology (k=6, p=0.12). Local clustering combined with long-range shortcuts enables rapid belief diffusion.
Figure 3
Tipping surfaces showing critical communication ratio vs. connectivity, as a function of graph size, randomness, listen ratio, and max rounds.
Figure 5
Tipping ridge comparison across four population archetypes. Democratic populations maintain lower thresholds across most connectivity levels.
Schematic recreations. Export real figures from the simulation scripts to replace these.
Full Report
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