2 citations · 2 across the 2 of their papers we have counts for
3 papers
Exploiting homogeneity for the optimal control of discrete-time systems: application to value iteration
Mathieu Granzotto, Romain Postoyan, Lucian Buşoniu +2
To investigate solutions of (near-)optimal control problems, we extend and exploit a notion of homogeneity recently proposed in the literature for discrete-time systems. Assuming t…
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…
Optimistic planning for the near-optimal control of nonlinear switched discrete-time systems with stability guarantees
Mathieu Granzotto, Romain Postoyan, Lucian Buşoniu +2
Originating in the artificial intelligence literature, optimistic planning (OP) is an algorithm that generates near-optimal control inputs for generic nonlinear discrete-time syste…