12 citations · 18 across the 25 of their papers we have counts for
3 papers · 1 filter
When to stop value iteration: stability and near-optimality versus computation
Mathieu Granzotto, Romain Postoyan, Dragan Nešić +2
Value iteration (VI) is a ubiquitous algorithm for optimal control, planning, and reinforcement learning schemes. Under the right assumptions, VI is a vital tool to generate inputs…
Active Learning for Linear Parameter-Varying System Identification
Robert Chin, Alejandro I. Maass, Nalika Ulapane +5
Active learning is proposed for selection of the next operating points in the design of experiments, for identifying linear parameter-varying systems. We extend existing approaches…
Tuning of multivariable model predictive controllersthrough expert bandit feedback
Alex. S. Ira, Chris Manzie, Iman Shames +4
For certain industrial control applications an explicit function capturing the nontrivial trade-off between competing objectives in closed loop performance is not available. In suc…