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SUMMARY:Learning and Collaboration in Human-AI Teams - Stefano V. Albrecht
  (DeepFlow)
DTSTART:20251111T155000Z
DTEND:20251111T163000Z
UID:TALK238480@talks.cam.ac.uk
DESCRIPTION:Multi-agent systems are a core area of AI where multiple auton
 omous agents coordinate and collaborate to solve complex problems. This ta
 lk will present our research across two key approaches to multi-agent coor
 dination. First\, we will discuss our work in multi-agent reinforcement le
 arning (MARL)\, including state-of-the-art algorithms for complex coordina
 tion challenges and their applications in domains such as multi-robot ware
 houses and strategic games like Starcraft and Go. Second\, we will explore
  recent advances in LLM-based multi-agent systems\, where large language m
 odels enable dynamic multi-agent teams to collaborate on complex workflows
  and tackle real-world problems. We will share our vision for a Manager Ag
 ent designed to achieve scalable and compliant orchestration of human-AI t
 eamwork.
LOCATION:Seminar Room 1\, Newton Institute
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