Combining Conflict-based Search and Agent-based Modeling for Evacuation Problems (Extended Abstract)

Kristýna Janovská, Pavel Surynek
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Abstract

We address the problem of evacuation from the heuristic search perspective combined with agent-based modeling (ABM). The evacuation problem is modeled as a navigation of multiple agents in a known environment. The environment is divided into a danger and a safe zone while the task of agents is to move from the danger zone to the safe zone in a collision-free manner. Unlike previous approaches that model the environment as a discrete graph with agents placed in its vertices, at most one agent per vertex, our approach adopts various continuous aspects such as a grid-based embedding of the environment into 2D space and continuous line of sight of agents. In addition to this, we adopt hierarchical structure of our multi-agent system in which so called leading agents are more informed and are capable of performing multi-agent pathfinding (MAPF) via centralized algorithms like conflict-based search (CBS) while so called following agents with limited knowledge about other agents are modeled using simple local rules. Our experimental evaluation indicates that suggested hierarchical modeling approach can serve as a tool for studying the progress and the efficiency of evacuation processes in different environments.
基于冲突搜索和基于agent建模的疏散问题(扩展摘要)
我们从启发式搜索的角度结合基于智能体的建模(ABM)来解决疏散问题。将疏散问题建模为已知环境中多个智能体的导航。环境被划分为危险区和安全区,agent的任务是以无碰撞的方式从危险区移动到安全区。与之前的方法不同,我们的方法采用了各种连续的方面,如基于网格的环境嵌入到二维空间中,以及代理的连续视线,这些方法将环境建模为一个离散图,每个顶点最多一个代理。除此之外,我们采用了多智能体系统的分层结构,其中所谓的领先智能体更了解情况,能够通过基于冲突的搜索(CBS)等集中算法执行多智能体寻路(MAPF),而所谓的跟随智能体对其他智能体的知识有限,使用简单的局部规则进行建模。实验结果表明,本文提出的分层建模方法可以作为研究不同环境下疏散过程的进度和效率的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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