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With the current ongoing debate about fairness, explainability and transparency of machine learning models, their application in high-impact clinical decision-making systems must be scrutinized. We consider a real-life example of risk…

Machine Learning · Computer Science 2020-11-13 Sandhya Tripathi , Bradley A. Fritz , Mohamed Abdelhack , Michael S. Avidan , Yixin Chen , Christopher R. King

Probabilistic justification logic is a modal logic with two kind of modalities: probability measures and explicit justification terms. We present a tableau procedure that can be used to decide the satisfiability problem for this logic in…

Logic in Computer Science · Computer Science 2017-08-15 Ioannis Kokkinis

In the ML fairness literature, there have been few investigations through the viewpoint of philosophy, a lens that encourages the critical evaluation of basic assumptions. The purpose of this paper is to use three ideas from the philosophy…

Computers and Society · Computer Science 2019-11-01 Samuel Deng , Achille Varzi

Three key properties that are desired of trustworthy machine learning models deployed in high-stakes environments are fairness, explainability, and an ability to account for various kinds of "drift". While drifts in model accuracy, for…

Machine Learning · Computer Science 2022-10-12 Shubham Sharma , Jette Henderson , Joydeep Ghosh

Runtime Verification deals with the question of whether a run of a system adheres to its specification. This paper studies runtime verification in the presence of partial knowledge about the observed run, particularly where input values may…

Logic in Computer Science · Computer Science 2022-07-13 Hannes Kallwies , Martin Leucker , Cesar Sanchez

We prove a general decomposition theorem for the modal $\mu$-calculus $L_\mu$ in the spirit of Feferman and Vaught's theorem for disjoint unions. In particular, we show that if a structure (i.e., transition system) is composed of two…

Logic · Mathematics 2014-05-12 Mikolaj Bojanczyk , Christoph Dittmann , Stephan Kreutzer

Transformer-based tabular foundation models have recently demonstrated promising in-context learning (ICL) performance on structured data, emerging as competitive alternatives to gradient-boosted trees. However, the fairness implications of…

Machine Learning · Computer Science 2026-01-06 Patrik Kenfack , Samira Ebrahimi Kahou , Ulrich Aïvodji

We provide a framework for compositional and iterative design and verification of systems with quantitative information, such as rewards, time or energy. It is based on disjunctive modal transition systems where we allow actions to bear…

Logic in Computer Science · Computer Science 2017-02-09 Uli Fahrenberg , Jan Křetínský , Axel Legay , Louis-Marie Traonouez

We introduce a causal framework for designing optimal policies that satisfy fairness constraints. We take a pragmatic approach asking what we can do with an action space available to us and only with access to historical data. We propose…

Machine Learning · Computer Science 2023-01-31 Limor Gultchin , Siyuan Guo , Alan Malek , Silvia Chiappa , Ricardo Silva

Undoing computations of a concurrent system is beneficial in many situations, e.g., in reversible debugging of multi-threaded programs and in recovery from errors due to optimistic execution in parallel discrete event simulation. A number…

Logic in Computer Science · Computer Science 2024-02-13 Ivan Lanese , Iain Phillips , Irek Ulidowski

We design a calculus for true concurrency called CTC, including its syntax and operational semantics. CTC has good properties modulo several kinds of strongly truly concurrent bisimulations and weakly truly concurrent bisimulations, such as…

Logic in Computer Science · Computer Science 2020-04-24 Yong Wang

We introduce a new notion of structural refinement, a sound abstraction of logical implication, for the modal nu-calculus. Using new translations between the modal nu-calculus and disjunctive modal transition systems, we show that these two…

Logic in Computer Science · Computer Science 2014-06-11 Uli Fahrenberg , Axel Legay , Louis-Marie Traonouez

In order to monitor and prevent bias in AI systems we can use a wide range of (statistical) fairness measures. However, it is mathematically impossible to optimize for all of these measures at the same time. In addition, optimizing a…

Artificial Intelligence · Computer Science 2023-07-18 Stefan Buijsman

Fairness in decision-making processes is often quantified using probabilistic metrics. However, these metrics may not fully capture the real-world consequences of unfairness. In this article, we adopt a utility-based approach to more…

Machine Learning · Computer Science 2024-06-19 Tolulope Fadina , Thorsten Schmidt

I investigate the modal commitments of various conceptions of the philosophy of arithmetic potentialism. Specifically, I shall consider the potentialist conceptions arising from a model-theoretic view of the models of arithmetic as possible…

Logic · Mathematics 2025-12-23 Joel David Hamkins

In this paper, we first propose a new liveness requirement for shared objects and data structures, we then give a shared queue algorithm that satisfies this requirement and we prove its correctness. We also implement this algorithm and…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-23 David Y. C. Chan , Shucheng Chi , Vassos Hadzilacos , Sam Toueg

Fairness is a critical concept in ethics and social domains, but it is also a challenging property to engineer in software systems. With the increasing use of machine learning in software systems, researchers have been developing techniques…

Software Engineering · Computer Science 2025-01-29 Giordano d'Aloisio , Claudio Di Sipio , Antinisca Di Marco , Davide Di Ruscio

In this paper, we deal with the problem of putting together modal worlds that operate in different logic systems. When evaluating a modal sentence $\Box \varphi$, we argue that it is not sufficient to inspect the truth of $\varphi$ in…

Logic · Mathematics 2022-03-02 Alfredo Roque Freire , Manuel A. Martins

In this paper we work on (bi)simulation semantics of processes that exhibit both nondeterministic and probabilistic behaviour. We propose a probabilistic extension of the modal mu-calculus and show how to derive characteristic formulae for…

Logic in Computer Science · Computer Science 2015-05-19 Yuxin Deng , Rob van Glabbeek

The modal mu-calculus is obtained by adding least and greatest fixed-point operators to modal logic. Its alternation hierarchy classifies the mu-formulas by their alternation depth: a measure of the codependence of their least and greatest…

Logic in Computer Science · Computer Science 2025-11-05 Leonardo Pacheco
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