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.

中文翻译：

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蚂蚁、机器人、人类：一种自组织的复杂系统建模方法

当今人类面临的大多数重大挑战都涉及复杂的基于代理的系统，例如流行病学、经济学或生态学。然而，确定其自组织能力背后的一般原则仍然是一项悬而未决的任务。本文提出了一种新颖的建模方法，能够自我部署系统结构和目标驱动代理的活动，这些代理可以采取适当的行动来实现其目标。人类、机器人和动物都被赋予了这种行为。基于系统特定目标依赖网络的信息，自组织被证明是从通用理性活动算法的决策中产生的。这种方法独特的自我部署功能，也可以应用于非目标驱动的代理，