BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//wp-events-plugin.com//7.3.5//EN
TZID:Europe/Paris
X-WR-TIMEZONE:Europe/Paris
BEGIN:VEVENT
UID:1132@cran.univ-lorraine.fr
DTSTART;TZID=Europe/Paris:20251009T140000
DTEND;TZID=Europe/Paris:20251009T150000
DTSTAMP:20250930T131818Z
URL:https://www.cran.univ-lorraine.fr/events/seminaire-de-mario-zanon/
SUMMARY:Séminaire de Mario Zanon
DESCRIPTION:Titre : Safe\, Stable\, and Explainable Reinforcement Learning\
 n\nRésumé :  RL is a very successful approach to optimal control\, whic
 h\, however\, struggles to provide explainability and strong guarantees on
  the behavior of the resulting control scheme. In contrast\, MPC is a stan
 dard tool for the closed-loop optimal control of complex systems with cons
 traints and limitations and benefits from a rich theory to assess closed-l
 oop behavior. Because of model inaccuracy\, however\, MPC can fail at deli
 vering satisfactory closed-loop performance. This seminar will discuss how
  to leverage the advantages of the two techniques\, offering a path toward
  safe and explainable RL.\n\nBiographie : Mario Zanon received the Master'
 s degree in Mechatronics from the University of Trento\, and the Diplôme 
 d'Ingénieur from the Ecole Centrale Paris\, in 2010. After research stays
  at the KU Leuven\, University of Bayreuth\, Chalmers University\, and the
  University of Freiburg he received the Ph.D. degree in Electrical Enginee
 ring from the KU Leuven in November 2015. He held a Post-Doc researcher po
 sition at Chalmers University until the end of 2017 and is now Associate P
 rofessor at the IMT School for Advanced Studies Lucca. His research intere
 sts include optimal control and estimation of nonlinear dynamic systems\, 
 in particular for aerospace and automotive applications\, economic MPC\, n
 umerical methods for optimization\, and reinforcement learning.\n\nLien Te
 ams: cliquer ici.
CATEGORIES:Département CID,Séminaire projet MODELE
LOCATION:CRAN - ENSEM\, 2\, Avenue de la Foret de Haye\, Voandoeuvre-les-Na
 ncy\, 54516\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=2\, Avenue de la Foret de H
 aye\, Voandoeuvre-les-Nancy\, 54516\, France;X-APPLE-RADIUS=100;X-TITLE=CR
 AN - ENSEM:geo:0,0
END:VEVENT
BEGIN:VTIMEZONE
TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:DAYLIGHT
DTSTART:20250330T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
END:DAYLIGHT
END:VTIMEZONE
END:VCALENDAR