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SUMMARY:A Multi-Agent System for Mathematical Discovery - Daattavya Aggarw
 al\, Department of Computer Science\, University of Cambridge
DTSTART:20250324T123000Z
DTEND:20250324T130000Z
UID:TALK229393@talks.cam.ac.uk
CONTACT:Sam Nallaperuma-Herzberg
DESCRIPTION:The practice of working mathematicians shows that the process 
 of discovering novel\, interesting mathematics often involves discussions 
 amongst multiple experts and making mistakes. Making false (yet interestin
 g) conjectures and failed attempts to prove them can be driving forces for
  progress in the field. Moreover\, there is an inherent social aspect to j
 udging both the correctness and value of research level math. In this talk
 \, I discuss our proposal for a multi-agent reinforcement learning archite
 cture that incorporates these aspects of the mathematical process\, aiming
  to learn interesting statements purely from mathematical data.
LOCATION:SS03 Seminar Room\, Willam Gates building (Department of Computer
  Science and Technology)
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