论文标题
蚂蚁，机器人，人类：一种自组织，复杂的系统建模方法
Ants, robots, humans: a self-organizing, complex systems modeling approach
论文作者
论文摘要
当今人类的大多数宏伟挑战都涉及基于复杂的代理系统，例如流行病学，经济学或生态学。但是，仍然是待处理任务的挑战，即确定其自我组织能力的一般原则。本文提出了一种新颖的建模方法，能够自欺欺人，以自我欺骗，以实现目标驱动的代理人的系统结构和活动，以实现其目标。人类，机器人和动物都具有这种行为。根据系统特定目标依赖性网络的信息，自组织表明从通用合理活动算法的决策中得出了自我组织。这种方法的独特自我部署功能也可以应用于非目标驱动的代理，可以大大提高基于代理建模的应用的范围和深度。
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.
