アリ・ロボット・人間：自己組織化する複雑系モデリングへの統一アプローチ
Ants, robots, humans: a self-organizing, complex systems modeling approach
ゴール駆動型エージェントの構造と行動を自己展開させる共通の合理的活動アルゴリズムを提案し、自己組織化がゴール依存ネットワークの情報から創発することを示した。
著者: Martin Jaraiz
分類: q-fin.GN, cs.RO
原文アブストラクト
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.