Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Adaptive Task Allocation Inspired by a Model of Division of Labor in Social Insects
Biocomputing and emergent computation: Proceedings of BCEC97
Computing in Science and Engineering
Swarm-Bot: A New Distributed Robotic Concept
Autonomous Robots
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Evolving preferences among emergent groups of agents
Adaptive agents and multi-agent systems
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In this study, we investigate self-organizing social hierarchies in multi-agent systems. Agents occupy the nodes of a small-world network and interact exclusively with other agents in their local neighbourhood. Here, the interactions represent competition for a limited resource. Monte-Carlo simulations show that the changes in a network's structure can alter the steady-state attributes for fixed reward/penalty mechanisms. The results suggest that the expected phase transition from a homogeneous to a hierarchical society depends on: (a) the relative strengths of the feedback mechanisms employed, (b) the underlying communication topology, and (c) whether previously dominated agents are replaced in the population by agents with higher social status. A key contribution of this paper is the coherent picture painted of the relationship between social differentiation and spatial structure in a multi-agent system.