most citedA Unifying Formal Approach to Importance Values in Boolean Functions

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2023

Proceedings of the First Workshop on Trends in Configurable Systems Analysis

Maurice H. ter Beek, Clemens Dubslaff

The analysis of configurable systems, i.e., systems those behaviors depend on parameters or support various features, is challenging due to the exponential blowup arising in the nu…

cs.GT20232 cited

A Unifying Formal Approach to Importance Values in Boolean Functions

Hans Harder, Simon Jantsch, Christel Baier +1

Boolean functions and their representation through logics, circuits, machine learning classifiers, or binary decision diagrams (BDDs) play a central role in the design and analysis…

cs.LG2023

More for Less: Safe Policy Improvement With Stronger Performance Guarantees

Patrick Wienhöft, Marnix Suilen, Thiago D. Simão +3

In an offline reinforcement learning setting, the safe policy improvement (SPI) problem aims to improve the performance of a behavior policy according to which sample data has been…

cs.LG2023

Strategy Synthesis in Markov Decision Processes Under Limited Sampling Access

Christel Baier, Clemens Dubslaff, Patrick Wienhöft +1

A central task in control theory, artificial intelligence, and formal methods is to synthesize reward-maximizing strategies for agents that operate in partially unknown environment…

cs.AI2023

On the Foundations of Cycles in Bayesian Networks

Christel Baier, Clemens Dubslaff, Holger Hermanns +1

Bayesian networks (BNs) are a probabilistic graphical model widely used for representing expert knowledge and reasoning under uncertainty. Traditionally, they are based on directed…