Multiple pursuers TrailMax algorithm for dynamic environments

Afzalov, Azizkhon; Lotfi, Ahmad; Inden, Benjamin; Aydin, Mehmet

Abstract

Multi-agent multi-target search problems, where the targets are capable of movement, require sophisticated algorithms for near-optimal performance. While there are several algorithms for agent control, comparatively less attention has been paid to near-optimal target behaviours. Here, a state-of-the-art algorithm for targets to avoid a single agent called TrailMax has been adapted to work within a multiple agents and multiple targets framework. The aim of the presented algorithm is to make the targets avoid capture as long as possible, if possible until timeout. Empirical analysis is performed on grid-based gaming benchmarks. The results suggest that Multiple Pursuers TrailMax reduces the agent success rate by up to 15% as compared to several previously used target control algorithms and increases the time until capture in successful runs.

Citation

Afzalov, A., Lotfi, A., Inden, B., & Aydin, M. (2021). Multiple pursuers TrailMax algorithm for dynamic environments. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART (437-443). https://doi.org/10.5220/0010392404370443

• Conference Name: 13th International Conference on Agents and Artificial Intelligence
• Conference Location: Online
• Start Date: Feb 4, 2021
• End Date: Feb 6, 2021
• Acceptance Date: Dec 18, 2020
• Online Publication Date: Mar 10, 2021
• Publication Date: Feb 4, 2021
• Deposit Date: Mar 11, 2021
• Publicly Available Date: Mar 19, 2021
• Volume: 2
• Pages: 437-443
• Book Title: Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
• ISBN: 9789897584848
• DOI: https://doi.org/10.5220/0010392404370443
• Public URL: https://uwe-repository.worktribe.com/output/7196272