Authors:
Róbert Selvek
and
Pavel Surynek
Affiliation:
Faculty of Information Technology, Czech Technical University in Prague, Thákurova 9, 160 00 Praha 6 and Czech Republic
Keyword(s):
Evacuation Planning, Cooperative Path-finding, Local Algorithms, Simulations, Real-life Scenarios.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Domain Analysis and Modeling
;
Health Engineering and Technology Applications
;
Human-Machine Cooperation
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
This paper addresses evacuation problems from the perspective of cooperative path finding (CPF). The evacuation problem we call multi-agent evacuation (MAE) consists of an undirected graph and a set of agents. The task is to move agents from the endangered part of the graph into the safe part as quickly as possible. Although there exist centralized evacuation algorithms based on network flows that are optimal with respect to various objectives, such algorithms would hardly be applicable in practice since real agents will not be able to follow the centrally created plan. Therefore we designed a local evacuation planning algorithm called LC-MAE based on local CPF techniques. Agent-based simulations in multiple real-life scenarios show that LC-MAE produces solutions that are only worse than the optimum by a small factor. Moreover our approach led to important findings about how many agents need to behave rationally to increase the speed of evacuation.