With the growing interest in leveraging space technologies to provide both knowledge and
services, the need for efficient space mission management also increases. Among all the …

We investigate the use of multi-agent allocation techniques on problems related to Earth
observation scenarios with multiple users and satellites. We focus on the problem of …

Target sequencing is an important aspect of agile Earth-observing satellite scheduling. The
objective of the problem is to find a feasible imaging sequence that maximizes the …

Reinforcement learning (RL) is a highly adaptable framework for generating autonomous
agents across a wide domain of problems. While RL has been successfully applied to highly …

Advances in target scheduling algorithms are necessary to fully utilize the capabilities of
agile Earth-observing satellites. While most current approaches preplan sequences of target …

Earth observation resources are becoming increasingly indispensable in disaster relief,
damage assessment, and other related domains. Many unpredictable factors, such as …

Earth observation satellites (EOS) are satellites equipped with optical sensors that orbit the
Earth to take photographs of particular areas at the request of users. With the development …

Multi-agent systems (MAS) are increasingly applied to complex task allocation in two-sided
markets, where agents such as companies and customers interact dynamically. Traditional …

We envision a multi-agent federation layer to coordinate systems composed of independent
Earth observation missions. The goal of this federation is to allow clients requesting …

The imaging tasks performed by Earth Observation Satellites (EOSs) are highly dynamic in
terms of task success uncertainties arising from sensor malfunctions or weather conditions …