6 citations · 11 across the 3 of their papers we have counts for
3 papers
Improved bound on the worst case complexity of Policy Iteration
Romain Hollanders, Balázs Gerencsér, Jean-Charles Delvenne +1
Solving Markov Decision Processes (MDPs) is a recurrent task in engineering. Even though it is known that solutions for minimizing the infinite horizon expected reward can be found…
A complexity analysis of Policy Iteration through combinatorial matrices arising from Unique Sink Orientations
Romain Hollanders, Balázs Gerencsér, Jean-Charles Delvenne +1
Unique Sink Orientations (USOs) are an appealing abstraction of several major optimization problems of applied mathematics such as for instance Linear Programming (LP), Markov Deci…
Policy Iteration is well suited to optimize PageRank
Romain Hollanders, Jean-Charles Delvenne, Raphaël Jungers
The question of knowing whether the policy Iteration algorithm (PI) for solving Markov Decision Processes (MDPs) has exponential or (strongly) polynomial complexity has attracted m…