11 citations · 44 across the 14 of their papers we have counts for
19 papers
Alternating Good-for-MDP Automata
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
When omega-regular objectives were first proposed in model-free reinforcement learning (RL) for controlling MDPs, deterministic Rabin automata were used in an attempt to provide a…
Mungojerrie: Reinforcement Learning of Linear-Time Objectives
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
Reinforcement learning synthesizes controllers without prior knowledge of the system. At each timestep, a reward is given. The controllers optimize the discounted sum of these rewa…
Model-free Reinforcement Learning for Branching Markov Decision Processes
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
We study reinforcement learning for the optimal control of Branching Markov Decision Processes (BMDPs), a natural extension of (multitype) Branching Markov Chains (BMCs). The state…
Priority Promotion with Parysian Flair
Massimo Benerecetti, Daniele Dell'Erba, Fabio Mogavero +2
We develop an algorithm that combines the advantages of priority promotion - one of the leading approaches to solving large parity games in practice - with the quasi-polynomial tim…
Facility Reallocation on the Line
Bart de Keijzer, Dominik Wojtczak
We consider a multi-stage facility reallocation problems on the real line, where a facility is being moved between time stages based on the locations reported by agents. The ai…
Simple Stochastic Games with Almost-Sure Energy-Parity Objectives are in NP and coNP
Richard Mayr, Sven Schewe, Patrick Totzke +1
We study stochastic games with energy-parity objectives, which combine quantitative rewards with a qualitative -regular condition: The maximizer aims to avoid running out of ene…