BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Mika Persson (Chalmers & GU) DTSTART:20241202T121500Z DTEND:20241202T130000Z DTSTAMP:20260417T004337Z UID:cam/47 DESCRIPTION:Title: Dec entralized control of teams of drones: A mixed collaborative/competitive g ame\nby Mika Persson (Chalmers & GU) as part of CAM seminar\n\nLecture held in MV:L14.\n\nAbstract\nSmall and inexpensive drones are increasingl y used in surveillance\, reconnaissance\, and attack operations. Future dr ones are expected to operate autonomously in large swarms\, posing challen ges for traditional Surface-Based Air Defense (SBAD) systems\, which rely on radar sensors and effectors like missiles or jamming. Swarms can overwh elm SBAD systems due to their sheer numbers and economic asymmetry\, as dr ones are significantly cheaper than defense systems. A potential counterme asure is deploying defensive swarms of small drones with sensors and effec tors\, necessitating optimized swarm behavior and capability evaluation. T he proposed project focuses on decentralized control of such swarms using game theory\, addressing challenges in operational goal representation\, s ituational awareness through sensing and communication\, and managing unce rtainty about enemy capabilities. These challenges are modeled by Partiall y Observable Stochastic Games. Approximation techniques like Multi-Agent R einforcement Learning are explored\, leveraging algorithms like MADDPG and MAAC for mixed competitive and collaborative swarm-versus-swarm scenarios . While related works address components of the problem\, they fall short of addressing the full complexity\, particularly in handling unknown drone numbers\, controlled sensing\, communication\, and intelligent adversarie s in a competitive game-theoretic framework.\n LOCATION:https://researchseminars.org/talk/cam/47/ END:VEVENT END:VCALENDAR