Abstract
The paper dwells on solution to the problem of planning large-scale space observation systems, which can include from several dozens to hundreds of small spacecrafts. These systems are created in response to massive increase in the load on currently operating systems. New space systems, in comparison with traditional single spacecrafts, impose much more tough requirements on methods of planning, and only a few of the existing solutions can at least partially correspond to them. Thus, there is a need for new planning approaches that take into account domain semantics more deeply. The paper presents expanded application of multi-agent technology. Its essence lies in negotiations between agents of imaging through mutual compromises and concessions. The desired efficiency is achieved by searching for the near-to-global optimum for each application and using this information in a targeted search for a solution for the entire system. Experiments have demonstrated that approach helps promptly draw up a schedule for dozens of spacecrafts and thousands of observation objects.
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Acknowledgements
The paper has been prepared based on materials of scientific research within the subsidized state theme of the Samara Federal Research Scientific Center RAS, Institute for Control of Complex Systems RAS for research and development on the topic: № AAAA-A19-119030190053-2 “Research and development of methods and means of analytical design, computer-based knowledge representation, computational algorithms and multi-agent technology in problems of optimizing management processes in complex systems”.
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Skobelev, P., Simonova, E., Galuzin, V., Galitskaya, A., Travin, V. (2021). Swarm of Satellites: Implementation and Experimental Study of Multi-Agent Solution for Adaptive Scheduling of Large-Scale Space Observation Systems. In: Dignum, F., Corchado, J.M., De La Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection. PAAMS 2021. Lecture Notes in Computer Science(), vol 12946. Springer, Cham. https://doi.org/10.1007/978-3-030-85739-4_22
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