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UID:20260617T054311EDT-3239ujpkJ4@132.216.98.100
DTSTAMP:20260617T094311Z
DESCRIPTION:Virtual Informal Systems Seminar (VISS) Centre for Intelligent 
 Machines (CIM) and Groupe d'Etudes et de Recherche en Analyse des Decision
 s (GERAD)\n	\n	Zoom Link\n	Meeting ID: 910 7928 6959        \n	Passcode: VISS
 \n	\n	Speaker: Margaret P. Chapman\, Assistant Professor\, Department of Ele
 ctrical and Computer Engineering\, University of Toronto\n\n\n	Abstract: \n
 \n	Risk-sensitive safety analysis is a safety analysis method for stochasti
 c systems on Borel spaces that uses a risk functional from finance called 
 Conditional Value-at-Risk (CVaR). CVaR provides a particularly expressive 
 way to quantify the safety of a control system\, as it represents the aver
 age cost in a fraction of worst cases. We define the notion of a risk-sens
 itive safe set in terms of a non-standard optimal control problem\, in whi
 ch a maximum cost is assessed via CVaR. We present a method to compute ris
 k-sensitive safe sets exactly in principle by utilizing a state-space augm
 entation technique\, and we provide a measurable selection condition to gu
 arantee the existence of an optimal pre-commitment policy. The proposed fr
 amework assumes continuous system dynamics and cost functions but is other
 wise flexible. In particular\, it can accommodate probabilistic control po
 licies\, fairly general disturbance distributions\, and control-dependent\
 , non-monotonic\, and non-convex stage costs. In addition\, we present a m
 ethod to compute under-approximations to risk-sensitive safe sets\, which 
 substantially improves computational tractability. We demonstrate how risk
 -sensitive safety analysis is useful for a stormwater infrastructure appli
 cation. Our numerical examples are inspired by current challenges that cit
 ies face in managing precipitation uncertainty.\n		\n		Biography: \n\n	Margaret
  Chapman is an Assistant Professor in the Department of Electrical and Com
 puter Engineering at the University of Toronto\, which she joined in July 
 2020. Her research focuses on risk-sensitive and stochastic control\, with
  emphasis on safety analysis and applications in healthcare and sustainabl
 e cities. She earned her BS degree with Distinction and MS degree in Mecha
 nical Engineering from Stanford University in 2012 and 2014\, respectively
 . Margaret earned her PhD degree in Electrical Engineering and Computer Sc
 iences from the University of California Berkeley (UC Berkeley) in August 
 2020. In 2021\, Margaret received a Leon O. Chua Award for outstanding ach
 ievement in nonlinear science from her doctoral alma mater. In addition\, 
 she is a recipient of a US National Science Foundation Graduate Research F
 ellowship\, Berkeley Fellowship for Graduate Study\, a Fulbright Scholarsh
 ip (granted by the US Department of State)\, and a Stanford University Ter
 man Engineering Scholastic Award.\n\n
DTSTART:20210604T140000Z
DTEND:20210604T150000Z
LOCATION:CA\, ZOOM
SUMMARY:Risk-Sensitive Safety Analysis via Conditional Value-at-Risk
URL:/cim/channels/event/risk-sensitive-safety-analysis
 -conditional-value-risk-331266
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