Combining Conflict-based Search and Agent-based Modeling for Evacuation Problems (Extended Abstract)
Autoři
Janovská, K.; Surynek, P.
Rok
2022
Publikováno
Proceedings of the Fifteenth International Symposium on Combinatorial Search. Palo Alto, California: Association for the Advancement of Artificial Intelligence (AAAI), 2022. p. 294-296. vol. 15. ISBN 978-1-57735-873-2.
Typ
Stať ve sborníku
Pracoviště
Anotace
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.
Hierarchical Control of Swarms during Evacuation
Autoři
Janovská, K.; Surynek, P.
Rok
2021
Publikováno
Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Setùbal: SciTePress, 2021. p. 61-73. vol. 2. ISSN 2184-3228. ISBN 978-989-758-533-3.
Typ
Stať ve sborníku
Pracoviště
Anotace
The problem of evacuation is addressed from the perspective of agent-based modeling (ABM) in this paper. We study evacuation as a problem of 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 one. Unlike previous approaches that model the environment as a discrete graph with agents placed in its vertices our approach adopts various continuous aspects such as grid-based embedding of the environment into 2D space continuous line of sight of an agent. In addition to this, we adopt hierarchical structure of multi-agent system in which so called leading agents are more informed and are capable of performing multiagent pathfinding (MAPF) via centralized algorithms like conflict-based search (CBS) while so called follower agents are modeled using simple local rules. Our experimental evaluation indicates that suggested modeling approach can serve as a tool for studying the progress and the efficiency of the evacuation process.