Weakest precondition inference for non-deterministic linear array programs
Precondition inference is an important problem with many applications. Existing
precondition inference techniques for programs with arrays have limited ability to find and …
precondition inference techniques for programs with arrays have limited ability to find and …
The AI Act and some implications for develo** AI-based systems
M Leucker - The Combined Power of Research, Education, and …, 2024 - Springer
This paper presents several challenges when develo** AI-based software systems for
potentially safety-critical domains in the European jurisdiction. Starting with the legal …
potentially safety-critical domains in the European jurisdiction. Starting with the legal …
Policies Grow on Trees: Model Checking Families of MDPs
Markov decision processes (MDPs) provide a fundamental model for sequential decision
making under process uncertainty. A classical synthesis task is to compute for a given MDP …
making under process uncertainty. A classical synthesis task is to compute for a given MDP …
Explainable Finite-Memory Policies for Partially Observable Markov Decision Processes
Partially Observable Markov Decision Processes (POMDPs) are a fundamental framework
for decision-making under uncertainty and partial observability. Since in general optimal …
for decision-making under uncertainty and partial observability. Since in general optimal …
Tools and Algorithms for the Construction and Analysis of Systems LNCS 14571
B Finkbeiner, L Kovács - Springer
This three-volume proceedings contains the papers presented at the 30th International
Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS …
Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS …