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SUMMARY:BMI Thesis Prize 2025 Seminar // Alberto Chiappa: Musculoskeletal 
 motor control with reinforcement learning
DTSTART:20260121T121500
DTEND:20260121T131500
DTSTAMP:20260503T060800Z
UID:3eb361787bc6e47865dc2431cd6fbbf71876e150a0b788de170a11c9
CATEGORIES:Conferences - Seminars
DESCRIPTION:Alberto Chiappa\, BMI\nAnimals\, including humans\, interact w
 ith the external environment primarily through motion. Replicating their m
 otor control skills in artificial embodied agents is a major objective of 
 artificial intelligence research. Using biologically realistic computation
 al models of the human musculoskeletal system\, we can study motor skill l
 earning and adaptation in simulation with unprecedented detail and efficie
 ncy. Advanced biomechanical simulators allow us to train policies that hav
 e to deal with the complexity and high-dimensionality of biological motor 
 control. This talk presents a collection of studies focused on different a
 spects of artificial embodied intelligence\, linked by one common underlyi
 ng research question: the learnability of human-level motor control polici
 es.\n 
LOCATION:SV 1717 https://plan.epfl.ch/?room==SV%201717 https://epfl.zoom.u
 s/j/64813563657
STATUS:CONFIRMED
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