Ant-like missionaries and cannibals: synthetic pheromones for distributed motion control
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Entropy and self-organization in multi-agent systems
Proceedings of the fifth international conference on Autonomous agents
Business Dynamics
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Ant Colony Optimization
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Division of labor in a group of robots inspired by ants' foraging behavior
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
A survey of autonomic communications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Pervasive pheromone-based interaction with RFID tags
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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The dynamic interactions of interdependent components in complex, adaptive, self-organizing systems CASOS often seem to sequester system entropy or uncertainty through distributed, as opposed to central, control. This article presents a system dynamics SD simulation model that not only replicates self-organizing system uncertainty results, but also looks at self-organization causally. The model analysis articulates how circular causal pathways or feedback loops in CASOS produce nonlinear dynamics spontaneously out of local interactions. The SD simulation and model analysis results show exactly how distributed control leads positive feedback to explosive growth, which ends when all dynamics have been absorbed into an attractor, leaving the system in a stable, negative feedback state. Cast as a methodological contribution, the article's SD model analysis explains why phenomena of interest emerge in agent-based models, a topic crucial in understanding and designing CASOS. Moreover, CASOS concepts inspired by nature and biology can motivate biologically-inspired IS research.