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DTSTAMP:20231107T003639Z
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DTSTART;TZID=America/New_York:20231106T183000
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DESCRIPTION:Autonomous multi-agent UAV and UGV systems are promising for cr
 itical applications such as disaster response\, logistics and transportati
 on\, supplementing cellular networks\, agricultural sensing\, environmenta
 l monitoring\, and security and military operations. Achieving the desired
  multi-agent collaborative behaviors requires joint perception and informa
 tion sharing over wireless links. In this talk we look at recent progress 
 on graph neural network (GNN) approaches for learning perception-action-co
 ntrol (PAC) loops. This includes learning what information to share among 
 agents that supports a team objective. Going forward\, many issues arise\,
  including how to combine learning and model-based control\, achieving sca
 lability and resilient group behavior\, and melding mobility and networkin
 g. The combination of learning\, modeling\, and cognitive networking is a 
 promising path to collaborative intelligent systems.\n\nSpeaker(s): Brian 
 M. Sadler\, \n\nAgenda: \n6:30 PM Welcome and introduction\n6:35 PM Presen
 tation\n7:20 PM Q&A\n7:30 PM Conclude\n\nVirtual: https://events.vtools.ie
 ee.org/m/380463
LOCATION:Virtual: https://events.vtools.ieee.org/m/380463
ORGANIZER:d.herres@ieee.org
SEQUENCE:23
SUMMARY:Collaborative Autonomy\, GNNs\, and Spectrum
URL;VALUE=URI:https://events.vtools.ieee.org/m/380463
X-ALT-DESC:Description: <br /><p>Autonomous multi-agent UAV and UGV systems
  are promising for critical applications such as disaster response\, logis
 tics and transportation\, supplementing cellular networks\, agricultural s
 ensing\, environmental monitoring\, and security and military operations.&
 nbsp\; Achieving the desired multi-agent collaborative behaviors requires 
 joint perception and information sharing over wireless links. In this talk
  we look at recent progress on graph neural network (GNN) approaches for l
 earning perception-action-control (PAC) loops.&nbsp\; This includes learni
 ng what information to share among agents that supports a team objective. 
 Going forward\, many issues arise\, including how to combine learning and 
 model-based control\, achieving scalability and resilient group behavior\,
  and melding mobility and networking. The combination of learning\, modeli
 ng\, and cognitive networking is a promising path to collaborative intelli
 gent systems.</p><br /><br />Agenda: <br /><p>6:30 PM&nbsp\; Welcome and i
 ntroduction<br />6:35 PM&nbsp\; Presentation<br />7:20 PM Q&amp\;A<br />7:
 30 PM Conclude</p>
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