22 citations · 44 across the 8 of their papers we have counts for
5 papers · 1 filter
Output-decomposed Learning of Mealy Machines
Rick Koenders, Joshua Moerman
We present an active automata learning algorithm which learns a decomposition of a finite state machine, based on projecting onto individual outputs. This is dual to a recent compo…
Gradient-Descent for Randomized Controllers under Partial Observability
Linus Heck, Jip Spel, Sebastian Junges +2
Randomization is a powerful technique to create robust controllers, in particular in partially observable settings. The degrees of randomization have a significant impact on the sy…
Generating Functions for Probabilistic Programs
Lutz Klinkenberg, Kevin Batz, Benjamin Lucien Kaminski +3
This paper investigates the usage of generating functions (GFs) encoding measures over the program variables for reasoning about discrete probabilistic programs. To that end, we de…
Separation and Renaming in Nominal Sets
Joshua Moerman, Jurriaan Rot
Nominal sets provide a foundation for reasoning about names. They are used primarily in syntax with binders, but also, e.g., to model automata over infinite alphabets. In this pape…
Fast Computations on Ordered Nominal Sets
David Venhoek, Joshua Moerman, Jurriaan Rot
We show how to compute efficiently with nominal sets over the total order symmetry, by developing a direct representation of such nominal sets and basic constructions thereon. In c…