Design and implementation of autonomous distributed network intelligence with evolution and coevolution
To realize exploration, surveying, container transportation and other activities within a lunar lava tube for which no environmental information has been obtained in advance, AI technologies such as multi-agent reinforcement learning will be used, designing network intelligence that will autonomously determine the roles and behavior of individuals and swarms, along with the necessary functionality.
To ensure adaptability to challenging environments, these functions will be designed as algorithms and systems that are able to take into account power consumption, communication distances, behavior under asynchronous conditions and other factors, and allocate roles within a swarm to handle individual performance differences, changes over time, damage and other eventualities.
Researchers
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Hiroaki KAWASHIMA
Professor, Graduate School of Information Science, University of Hyogo
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Yuya HIGASHIKAWA
Professor, Graduate School of Information Science, University of Hyogo
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Shuichi MIYAZAKI
Professor, Graduate School of Information Science, University of Hyogo
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Hiroaki OHSHIMA
Associate Professor, Graduate School of Information Science, University of Hyogo
