用仿生机器人模拟群体驱赶天敌行为，揭示协作机制与规模关系。
Go Big or Go Home: Simulating Mobbing Behavior with Braitenbergian Robots
- 通过模仿动物鸣叫召集同伴，实现机器人协同驱逐威胁。
- 十台机器人组比三台成功率高，远距离呼叫显著提升效果。
- 适用于人工生命系统和自主机器人控制架构设计研究。
我们使用Webots机器人仿真平台，模拟了由布赖滕贝格机器人组成的双人回避与群体围攻捕食者行为。群体围攻是一种反捕食适应行为，某些动物会合作攻击或骚扰捕食者以保护自身。一种协调群体围攻的方式是通过发出围攻叫声召唤同种个体。我们模仿该机制，让布赖滕贝格机器人在遭遇光源（代表无生命捕食者）时发出围攻叫声；若能召唤到同伴则围攻，否则逃逸。我们探讨了围攻叫声传播范围（无限、中等、低范围）和机器人小组规模（10台对比3台）对群体围攻成功率的影响。结果表明，两个变量均具有显著影响。本研究对人工生命中的行为选择仿真及自主代理控制架构设计具有启示意义。
原文摘要 · Abstract (English)
We used the Webots robotics simulation platform to simulate a dyadic avoiding and mobbing predator behavior in a group of Braitenbergian robots. Mobbing is an antipredator adaptation used by some animals in which the individuals cooperatively attack or harass a predator to protect themselves. One way of coordinating a mobbing attack is using mobbing calls to summon other individuals of the mobbing species. We imitated this mechanism and simulated Braitenbergian robots that use mobbing calls when they face a light source (representing an inanimate predator) and mob it if they can summon allies, otherwise, they escape from it. We explore the effects of range of mobbing call (infinite range, mid-range and low-range) and the size of the robot group (ten robots vs three) on the overall success of mobbing. Our results suggest that both variables have significant impacts. This work has implications for simulations of action selection in artificial life and designing control architectures for autonomous agents.
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