ASTS: Autonomous switching of task-level strategies

• Autorzy: Wang Xianchang , Lv Bingyu , Wang Kaiyu , Zhang Rui

Identyfikatory

DOI

10.34768/amcs-2023-0040

• Języki publikacji: EN

Abstrakty

EN

Autonomous coordination of multi-agent systems can improve the reaction and dispatching ability of multiple agents to emergency events. The existing research has mainly focused on the reactions or dispatching in specific scenarios. However, task-level coordination has not received significant attention. This study proposes a framework for autonomous switching of task-level strategies (ASTS), which can automatically switch strategies according to different scenarios in the task execution process. The framework is based on the blackboard system, which takes the form of an instance as an agent and the form of norm(s) as a strategy; it uses events to drive autonomous cooperation among multiple agents. A norm may be triggered when an event occurs. After the triggered norm is executed, it can change the data, state, and event in ASTS. To demonstrate the autonomy and switchability of the proposed framework, we develop a fire emergency reaction dispatch system. This system is applied to emergency scenarios involving fires. Five types of strategies and two control modes are designed for this system. Experiments show that this system can autonomously switch between different strategies and control modes in different scenarios with promising results. Our framework improves the adaptability and flexibility of multiple agents in an open environment and represents a solid step toward switching strategies at the task level.

Słowa kluczowe

EN

task level; autonomous switching strategy; blackboard system

PL

poziom zadania; strategia przełączania; system tablicowy

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2023
• Tom: Vol. 33, no. 4
• Strony: 553--568
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Wang Xianchang

• Institute of Computer Science and Technology, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China
• Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China
• Research and Development Department, Chengdu Kestrel Artificial Intelligence Institute, No. 17 Dayu East Road, Deyuan Jingrong Town, Pidu District, 611136, Chengdu, Sichuan, China

autor

Lv Bingyu

• Institute of Computer Science and Technology, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China
• Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China

autor

Wang Kaiyu

• Institute of Computer Science and Technology, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China
• Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China

autor

Zhang Rui

• Institute of Computer Science and Technology, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China
• Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, No. 2699 Qianjin Street, 130021 Changchun, Jilin, China

Bibliografia

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