动态多智能体协调:机器人警察

P. Beling, B.J. Beaulieu, I. Durham, R.H. McKinstrie, P. Shumate, K.G. Stamper, E.K. Verell
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引用次数: 6

摘要

我们开发了一个基于仿真的测试平台,研究人员可以使用它来比较自治代理分散协调算法的性能。我们考虑的特殊协调问题是一个被称为机器警察(或RoboCop)问题的追捕逃避游戏。在这个游戏中,一组特工代表警察试图抓住一个或多个逃跑的嫌疑人。游戏被限制在(有界的)矩形网格中。警察和嫌疑人都被限制在相邻的牢房内水平和垂直移动,警察在移动速度上有优势。我们假设集中控制是不可能的(因此每个代理必须自主地做出决策),代理之间的通信是不可能的,并且代理没有事先建立行动协议。我们开发了一些简单的启发式方法来确定智能体的运动,然后演示了测试平台可以用来分析和比较这些启发式方法的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic multi-agent coordination: RoboCops
We develop a simulation-based test bed that researchers can use to compare the performance of algorithms for decentralized coordination of autonomous agents. The particular coordination problem that we consider is a pursuit-evasion game known as the robotic cop (or RoboCop) problem. In this game, a group of agents representing the police attempt to capture one or more fleeing suspects. Play is restricted to a (bounded) rectangular grid of cells. Both the cops and suspect are restricted to horizontal and vertical movement to adjacent cells, with the cops enjoying an advantage in movement rate. We assume that centralized control is not possible (so each agent must make decisions autonomously), that communication between agents is not possible, and that protocols for actions have not been established in advance by the agents. We develop some simple heuristics for determining agent movement, and then demonstrate ways in which the test bed can be used to analyze and compare these heuristics.
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