TY - GEN
T1 - Towards Addressing Dynamic Multi-agent Task Allocation in Law Enforcement
AU - Tkach, Itshak
AU - Nelke, Sofia Amador
N1 - Publisher Copyright:
© 2022 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - To deal with the underlying heterogeneous law enforcement problem (LEPH), one needs to allocate police officers to dynamic tasks whose locations, arrival times, and importance levels are unknown a priory. Addressing this challenge and inspired by real police logs, this research aims to solve the LEPH problem by using and comparing three methods: Fisher market-based FMC_TAH+, swarm intelligence HDBA, and Simulated Annealing SA algorithms. The three methods were compared in this study for the performance measures that are commonly used by law enforcement authorities. The results indicate an advantage for FMC_TAH+ both in total utility and in the average arrival time to tasks. Also, compared respectively to HDBA and SA, FMC_TAH+ leads to 34% and 32% higher team utility in the highest shift workload.
AB - To deal with the underlying heterogeneous law enforcement problem (LEPH), one needs to allocate police officers to dynamic tasks whose locations, arrival times, and importance levels are unknown a priory. Addressing this challenge and inspired by real police logs, this research aims to solve the LEPH problem by using and comparing three methods: Fisher market-based FMC_TAH+, swarm intelligence HDBA, and Simulated Annealing SA algorithms. The three methods were compared in this study for the performance measures that are commonly used by law enforcement authorities. The results indicate an advantage for FMC_TAH+ both in total utility and in the average arrival time to tasks. Also, compared respectively to HDBA and SA, FMC_TAH+ leads to 34% and 32% higher team utility in the highest shift workload.
KW - Multi-agent systems
KW - artificial intelligence
KW - law enforcement problem
UR - http://www.scopus.com/inward/record.url?scp=85134290233&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85134290233
T3 - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
SP - 1950
EP - 1951
BT - International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
T2 - 21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022
Y2 - 9 May 2022 through 13 May 2022
ER -