Cooperation Networks: Endogeneity and Complexity
Simon Angus
Abstract
Insights from the Complex Systems literature are employed to develop a computational model of truly endogenous strategic network formation. Artificial Adaptive Agents, implemented as Finite State Automata (FSA), play a modified two-player IPD game with an option to further develop the interaction space as part of their strategy. Several insights result from this minor modification: first, I find that network formation is a necessary condition for cooperation to be sustainable but that both the frequency of interaction and the degree to which edge formation impacts agent mixing are both necessary conditions for cooperative networks. Second, within the FSA-modified IPD frame-work, a rich ecology of agents and network topologies is observed and described. Third, the system dynamics are investigated and reveal that initially simple dynamics with small interaction length between agents gives way to complex, a-periodic dynamics with self-organized critical properties when interaction lengths are increased by a single step.
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