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International Conference on Complex Systems (ICCS2006)

Cooperation networks: endogeneity and complexity

Simon Angus
Economics, Univeristy of NSW

This paper employs insights from Complex Systems literature to develop
a computational model of endogenous strategic network formation. Artificial
Adaptive Agents, implemented as finite state automata, play a modified
two-player Iterated Prisoner's Dilemma game with an option to further develop
the interaction space as part of their strategy. Several insights result from
this relatively 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, with consequent payoff symmetry and network `purity'
seen to be further contributors to robust cooperative networks. Third, the
dynamics of the strategic system under network formation are investigated and
show that initially simple dynamics with small interaction length between
agents gives way to complex, a-periodic dynamics when interaction lengths are
increased by a single step. Subsequent analysis of the developing network
topology through time shows scaling behaviour in both time and space,
indicating the attainment of a self-organised critical state, and thus
apparently driving the complex dynamics of the overall strategic system.

The full text of this paper is available here in PDF format

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