Mechanical Engineering
Accelerating Stochastic Simulation and Control with Learned Models of Mean Behavior
November 15, 2019
1:00 p.m. - 2:00 p.m. ET
160 Hall of Arts
Mechanical Engineering
November 15, 2019
1:00 p.m. - 2:00 p.m. ET
160 Hall of Arts
We will show how learned models and efficient sampling algorithms can be used to accelerate the numerical estimation of the mean behavior of stochastic systems, without introducing any approximation error. Two expensive stochastic simulations will be considered: atmospheric aerosols simulated directly at the particle level, and reinforcement learning for legged robot control. The aerosol simulations follow billions of particles in a 3D region, such as the Northern California DOE CARES campaign area, to enable the direct computation of climate-impacting aerosol optical and cloud condensation nuclei properties. For learning robot control, we simulate jumping and landing dynamics on the microsecond timescale to train nonlinear neural network feedback policies for single-leg jumping.
Speaker: Matthew West, Associate Professor, Department of Mechanical Science & Engineering, University of Illinois at Urbana-Champaign
May 1 2024
2:00 PM - 4:00 PM ET
Tech Spark
Tech Spark Engineering Expo
Tech Spark’s High Bay (Ansys Hall C01)
May 15 2024
2:00 PM - 3:00 PM ET
Bosch Spark Conference Room, Scott Hall
May 17 2024
8:00 AM ET
Carnegie Mellon University Africa
CMU-Africa's 11th Graduation Ceremony
Kigali Serena Hotel, KN 3 Ave Kigali, Rwanda