Manfred Droste

2papers

2 Papers

4.1CCApr 26
Fagin's Theorem for Semiring Turing Machines

Guillermo Badia, Manfred Droste, Thomas Eiter et al.

In recent years, quantitative complexity over semirings has been intensively investigated. In this context, Eiter and Kiesel (Semiring Reasoning Frameworks in AI and Their Computational Complexity, J. Artif. Intell. Res., 2023) introduced non-deterministic Turing Machines with semiring-weighted transitions (SRTMs) to capture the complexity of a manifold of semiring frameworks. Beyond computational complexity, they posed the question of how we can relate the computational power of SRTMs to logical expressiveness. While this question was partially addressed for a more limited machine model by Badia et al.\ (Logical characterizations of weighted complexity classes, MFCS, 2024), the full question remained open. To answer it, we present an improved version of Eiter and Kiesel's SRTM model of computation. First and foremost, this enables us to prove a Fagin Theorem for the SRTM model, i.e., we show that the quantitative complexity class $\text{NP}_\infty(R)$, which comprises non-deterministic polynomial time computability in the improved SRTM model over a commutative semiring $R$, is captured by a version of weighted existential second-order logic that allows for predicates interpreted as semiring-annotated relations over $R$. Furthermore, we argue that the new SRTM model is preferable over the original one and show that it reclaims some important results from Eiter and Kiesel (2023) that were flawed with respect to the latter.

9.2FLApr 19
Weighted Automata and Regular Expressions for Financial Systems

Manfred Droste, Vitaly Nürnberg

We introduce weighted finite finance automata (WFFA), a formal framework for modeling and analyzing quantitative properties of financial systems driven by uncertain economic variables such as stock prices, interest rates, and exchange rates. The model provides a compositional and language-theoretic approach to scenario-based financial analysis, enabling systematic evaluation of financial instruments and trading strategies. To specify such systems, we introduce weighted finance regular expressions, a declarative language for quantitative financial properties. We establish a Kleene-Schützenberger-type correspondence between WFFAs and weighted finance regular expressions, together with effective translation procedures between the two formalisms. On the algorithmic side, we investigate fundamental decision and optimization problems for WFFAs, including the computation of extremal payoffs, and identify expressive yet computationally tractable subclasses. These results provide a foundation for formal, compositional, and efficient analysis of financial systems under multiple market scenarios.