Movement-control algorithms of mobile agents for achieving their coordination in large-scale and complicated environments

2022 Fiscal Year Final Research Report

• Project/Area Number: 18K18031
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 60050:Software-related
• Research Institution: Kyushu Institute of Technology
• Principal Investigator: SHIBATA Masahiro 九州工業大学, 大学院情報工学研究院, 准教授 (10806095)
• Project Period (FY): 2018-04-01 – 2023-03-31
• Keywords: 自律分散システム / モバイルエージェント / 集合問題 / g-部分集合問題 / 均一配置問題 / 動的ネットワーク / 自律分散ロボット群

Outline of Final Research Achievements

In this project, for mobile agents that move in the network autonomously, I mainly focused on the g-partial gathering problem and the uniform deployment problem. The g-partial gathering problem requires agents to reach a configuration such that at least g agents or no agent exists at each node, and the uniform deployment problem requires agents to spread uniformly in the network. I proposed algorithms to solve these problems under the assumption such that agents do not have enough memory space or global knowledge, or communication links are temporarily unstable. By these methods, I completed designing several elements necessary for the establishment of a framework for agents' coordination even in large-scale and complicated environments.

Free Research Field

自律分散アルゴリズム

Academic Significance and Societal Importance of the Research Achievements

近年の自律分散システムは大規模化・複雑化が進行しており、ネットワークの一時的な故障は避けられない。また、従来のエージェントは多くのメモリ情報を有した状態でネットワーク中を動作し、このことは消費電力の増加にもつながる。本研究課題で得られた、少ないエージェントメモリや移動コストでg-部分集合問題や均一配置問題を解決するアルゴリズムの成果を適用すると、上記の問題を解決できることが期待できる。