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Temporal Logics and Probabilistic Model Checking for Weighted Structures

Subject Area Theoretical Computer Science
Term from 2016 to 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 289295178
 
Final Report Year 2024

Final Report Abstract

Automaton models with weight annotations for states or transitions are widely used as operational models for system analysis with respect to resource consumption and cost-benefit trade-offs. In the literature, various modal logics have been introduced to formalize requirements on accumulated weights along (fragments of) computation paths. For instance, the accumulation of non-negative weights can represent the total energy consumption of a task schedule or the total penalty incurred for missed deadlines, while weight functions with both negative and positive values can be used to model energy levels in batterypowered devices or the total profit or loss of a stock over a trading day. A key objective of the project was to investigate verification problems for discrete-time Markov models with one or more weight functions. The central preliminary work of the project proposal was a paper from 2014, which introduces an extension of linear temporal logic (LTL) with modalities for weight accumulation under regular side conditions and examines aspects of expressiveness, as well as the boundary between decidability and undecidability of the model-checking problem for finite transition systems, Markov chains, and Markov decision processes (MDPs) with multiple weight functions. The project focused on the following topics: (1) the investigation of model-checking problems for a branching-time logic defined analogously, which extends probabilistic computation tree logic (PCTL) with operators for the probabilities of weight-dependent path properties, (2) a prototype implementation of the algorithms from the paper as well as the algorithms developed in (1) and experimental studies, (3) algorithms for expectations of accumulated weights, particularly variants of the classical stochastic shortest-path problem, (4) algorithms for new long-run operators to formalize properties of the stationary behavior of MDPs.

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