Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
[15] Peer-to-Peer Architecture Case Study: Gnutella Network
P2P '01 Proceedings of the First International Conference on Peer-to-Peer Computing
Dynamical Processes on Complex Networks
Dynamical Processes on Complex Networks
Lectures on Complex Networks
Learning to coordinate in complex networks
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
IEEE Communications Magazine
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Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the agent processes it stems from. Up to now, linking the global networked dynamics to such agent mechanisms has remained elusive. Here we define an observable dynamic and use it to track the self-organization of cooperators when co-evolving with defectors in networked populations interacting via a Prisoner's Dilemma. Computations on homogeneous networks evolve towards the coexistence between cooperator and defector agents, while computations in heterogeneous networks lead to the coordination between them. We show how the global dynamics co-evolves with the motifs of cooperator agents in the population, the overall emergence of cooperation depending sensitively on this co-evolution.