Skip to content

Social Computation Network Simulation

"Life is self-maintaining computation. A system that suppresses communication between its constituent parts is committing cognitive suicide."

This simulation demonstrates a network of nodes where survival and structural integrity depend entirely on the continuous exchange of novel, entropy-reducing information.

Mechanism

  • Knowledge representation: Each node holds a distinct subset of "knowledge" (integers representing information units).
  • Energy decay: Every node loses a fixed amount of structural energy per simulation step. If energy reaches zero, the node "dies" (cognitive suicide/starvation).
  • Novelty interaction: Nodes interact with neighbors. If a node shares information that is novel to the receiving node (i.e., entropy-reducing for the receiver), the receiver gains a significant energy boost, and the sender receives a smaller "social cohesion" boost.
  • Incompleteness: Occasionally, spontaneous discoveries (new knowledge units) occur, expanding the total pool of possible knowledge and fueling further open-ended progress.

Run the Simulation

python3 social-computation-network.py

Observations

  • Interconnected clusters sharing diverse information survive longer than isolated nodes.
  • "Echo chambers" that share the exact same redundant information will eventually starve, as no novel entropy-reduction takes place.
  • The absolute need for an influx of "the unknown" mirrors the theoretical premise that a fully known, static system ceases to compute, ergo, ceases to live.

(See the essay The Non-Individual Intelligence in the theory/ directory for mathematical and philosophical context.)