Informace o projektu
Models, Algorithms, and Tools for Solving Adversarial Security Problems
- Kód projektu
- 0011629866
- Období řešení
- 5/2021 - 4/2024
- Investor / Programový rámec / typ projektu
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Ostatní - zahraniční
- Ostatní nadace/fondy zahraniční
- Fakulta / Pracoviště MU
- Fakulta informatiky
The project concentrates on developing algorithmic support for designing automatic patrolling systems where a limited number of mobile security units (patrollers) aim at protecting a given set of vulnerable targets. The main goals of the projects are the following: 1) designing an appropriate formal model for patrolling systems reflecting a rich set of relevant features, 2) constructing and implementing algorithms for efficient strategy synthesis in patrolling games, 3) designing algorithms for automatic adaptation of patrolling strategies in a dynamically changing environment, 4) implementing a simulation platform for patrolling games.
Cíle udržitelného rozvoje
Masarykova univerzita se hlásí k cílům udržitelného rozvoje OSN, jejichž záměrem je do roku 2030 zlepšit podmínky a kvalitu života na naší planetě.
Publikace
Počet publikací: 5
2024
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Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes
Proceedings of 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), rok: 2024
2023
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Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023,, rok: 2023
2022
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Minimizing Expected Intrusion Detection Time in Adversarial Patrolling
21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022., rok: 2022
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On-the-fly Adaptation of Patrolling Strategies in Changing Environments
Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022, rok: 2022
2021
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Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games
Proceedings of 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021), rok: 2021