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Christel Baier

7 accepted papers

2026

Temporal Properties of Conditional Independence in Dynamic Bayesian Networks

AAAI 2026technical

Dynamic Bayesian networks (DBNs) are compact graphical representations used to model probabilistic systems where interdependent random variables and their distributions evolve over time. In this paper, we study the verification of the evolution of conditional-independence (CI) propositions against t

Cited by 0SourcePDFScholar
2025

Formal Quality Measures for Predictors in Markov Decision Processes

AAAI 2025technical

In adaptive systems, predictors are used to anticipate changes in the system’s state or behavior that may require system adaption, e.g., changing its configuration or adjusting resource allocation. Therefore, the quality of predictors is crucial for the overall reliability and performance of the sys…

Cited by 1SourcePDFScholar
2024

Backward Responsibility in Transition Systems Using General Power Indices

AAAI 2024technical

To improve reliability and the understanding of AI systems, there is increasing interest in the use of formal methods, e.g. model checking. Model checking tools produce a counterexample when a model does not satisfy a property. Understanding these counterexamples is critical for efficient debugging,…

2023

A Unifying Formal Approach to Importance Values in Boolean Functions

IJCAI 2023poster

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 of computing systems. Quantifying the relative impact of variables on the truth value by means of importance values can…

2023

More for Less: Safe Policy Improvement with Stronger Performance Guarantees

IJCAI 2023poster

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 generated. State-of-the-art approaches to SPI require a high number of samples to provide practical probabilistic guar…