51 citations · 366 across the 55 of their papers we have counts for
3 papers · 2 filters
Guessing Winning Policies in LTL Synthesis by Semantic Learning
Jan Kretinsky, Tobias Meggendorfer, Maximilian Prokop +1
We provide a learning-based technique for guessing a winning strategy in a parity game originating from an LTL synthesis problem. A cheaply obtained guess can be useful in several…
MULTIGAIN 2.0: MDP controller synthesis for multiple mean-payoff, LTL and steady-state constraints
Severin Bals, Alexandros Evangelidis, Jan Křetínský +1
We present MULTIGAIN 2.0, a major extension to the controller synthesis tool MULTIGAIN, built on top of the probabilistic model checker PRISM. This new version extends MULTIGAIN's…
Stopping Criteria for Value Iteration on Stochastic Games with Quantitative Objectives
Jan Křetínský, Tobias Meggendorfer, Maximilian Weininger
A classic solution technique for Markov decision processes (MDP) and stochastic games (SG) is value iteration (VI). Due to its good practical performance, this approximative approa…