NEWS  |  Ankush Chakrabarty gave an invited talk on machine learning for constrained control at AI for Engineering in Toronto

Date released: Aug 19, 2019


  •  NEWS   Ankush Chakrabarty gave an invited talk on machine learning for constrained control at AI for Engineering in Toronto
  • Date:

    August 19, 2019 - August 23, 2019

  • Description:

    Ankush Chakrabarty, a Visiting Research Scientist in MERL's Control and Dynamical Systems group, gave an invited talk at the AI for Engineering Summer School 2019 hosted by Autodesk. The talk briefly described MERL's research areas, and focused on Dr. Chakrabarty's work at MERL (with collaborators from the CD and DA group) on the use of supervised learning for verification of control systems with simulators/neural nets in the loop, and on constraint-enforcing reinforcement learning. Other speakers at the event included researchers from various academic and industrial research facilities including U Toronto, UW-Seattle, Carnegie Mellon U, the Vector Institute, and the Montreal Institute for Learning Algorithms.

  • Where:

    AI for Engineering Summer School 2019

  • MERL Contact:
  • External Link:

    https://www.ai4engineering.com/

  • Research Areas:

    Artificial Intelligence, Control, Dynamical Systems, Machine Learning

  • Related Publications:
  •  Chakrabarty, A., Quirynen, R., Danielson, C., Gao, W., "Approximate Dynamic Programming For Linear Systems with State and Input Constraints", European Control Conference (ECC), June 2019.
  •  Chakrabarty, A., Raghunathan, A.U., Di Cairano, S., Danielson, C., "Data-Driven Estimation of Reachable and Invariant Sets for Unmodeled Systems via Active Learning", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC.2018.8619646, December 2018.