Ants, robots, humans: a self-organizing, complex systems modeling approach

Martin Jaraiz

Abstract: Most of the grand challenges of humanity today involve complex agent-based systems, such as epidemiology, economics or ecology. However, remains as a pending task the challenge of identifying the general principles underlying their self-organizing capabilities. This article presents a novel modeling approach, capable to self-deploy both the system structure and the activities for goal-driven agents that can take appropriate actions to achieve their goals. Humans, robots, and animals are all endowed with this type of behavior. Self-organization is shown to emerge from the decisions of a common rational activity algorithm, based on the information of a system-specific goals dependency network. The unique self-deployment feature of this approach, that can also be applied to non-goal-driven agents, can boost considerably the range and depth of application of agent-based modeling.

Date: 2020-09, Revised 2020-10
New Economics Papers: this item is included in nep-cmp and nep-evo
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2009.10823

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