The project concentrates on algorithmic foundations of multi-agent systems accomplishing complex infinite-horizon objectives where the agents strive to fulfill recurring and uninterrupted tasks under risk and resilience constraints. Examples include atrolling/monitoring vulnerable targets, periodic service/maintenance at designated locations, reconnaissance, etc. Performing such activities in adversarial environment is risky, and responsible planning requires balancing the efficiency with overall risks. Furthermore,
the planning must be dynamic and instantly adapt to the new information discovered by the
agents and also unexpected changes in the environment and the swarm composition (some agents get broken, some locations become safer to move through, etc.). For large and hybrid swarms consisting of agents with different capabilities and different risk tolerance (drones, unmanned surface vehicles, human personnel, etc.), the above tasks require efficient and reliable computer-aided decision support. However, most of the current multi-agent swarm technologies/applications aim at completing one-time tasks within a relatively short time horizon, such as achieving a given formation or moving the swarm from one place
to another. The conceptual and algorithmic foundations for infinite-horizon objectives are not developed sufficiently, and the methodology/technology for the dynamic strategy adaptation is basically non-existing.
The proposed project concentrates on developing the missing foundations and algorithms, and demonstrating

Sustainable Development Goals

Masaryk University is committed to the UN Sustainable Development Goals, which aim to improve the conditions and quality of life on our planet by 2030.