Abstract
Influence systems seek to model how influence, broadly defined, spreads across a dynamic network. We build a general analytical framework which we then use to prove that, while Turing-complete, influence dynamics of the diffusive type is almost surely asymptotically periodic. In addition to resolving the dynamics of a widely used family of multiagent systems, we introduce a general renormalization method for the bifurcation analysis of multiagent systems.
Original language | English (US) |
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Pages (from-to) | 1403-1442 |
Number of pages | 40 |
Journal | SIAM Journal on Computing |
Volume | 44 |
Issue number | 5 |
DOIs | |
State | Published - Jan 1 2015 |
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Mathematics(all)
Keywords
- Chaos
- Dynamic networks
- Dynamical systems
- Influence systems
- Limit cycles
- Natural algorithms
- Renormalization