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Advancements in computer science and AI lead to the development of larger, more complex knowledge bases. These are susceptible to contradictions, particularly when multiple experts are involved. To ensure integrity during changes,…

Databases · Computer Science 2023-04-21 Stefan Decker

This paper addresses the quantitative verification of finite-time constrained occupation time for stochastic continuous-time systems governed by stochastic differential equations (SDEs). Unlike classical reachability analysis, which focuses…

Systems and Control · Electrical Eng. & Systems 2026-04-22 Bai Xue , C. -H. Luke Ong

Guaranteeing safe behavior on complex autonomous systems -- from cars to walking robots -- is challenging due to the inherently high dimensional nature of these systems and the corresponding complex models that may be difficult to determine…

Systems and Control · Electrical Eng. & Systems 2023-03-07 Tamas G. Molnar , Aaron D. Ames

We show that including degrees of a particular kind of provability in the search target for any theorem-prover in sufficiently powerful formal systems over finite-sized statements preserves well-definition and a sufficient consistency while…

Logic · Mathematics 2024-11-28 Rohan Bahl

This paper takes a step towards addressing the difficulty of constructing Control Barrier Functions (CBFs) for parallel safety boundaries. A single CBF for both boundaries has been reported to be difficult to validate for safety, and we…

Optimization and Control · Mathematics 2025-12-23 Kwang Hak Kim , Mamadou Diagne , Miroslav Krstić

In this paper, we consider lower bounds on the query complexity for testing CSPs in the bounded-degree model. First, for any ``symmetric'' predicate $P:{0,1}^{k} \to {0,1}$ except \equ where $k\geq 3$, we show that every (randomized)…

Data Structures and Algorithms · Computer Science 2010-07-21 Yuichi Yoshida

We propose new methods to synthesize control barrier function (CBF)-based safe controllers that avoid input saturation, which can cause safety violations. In particular, our method is created for high-dimensional, general nonlinear systems,…

Robotics · Computer Science 2022-11-22 Simin Liu , Changliu Liu , John Dolan

Random testing approaches work by generating inputs at random, or by selecting inputs randomly from some pre-defined operational profile. One long-standing question that arises in this and other testing contexts is as follows: When can we…

Software Engineering · Computer Science 2024-06-25 Neil Walkinshaw , Michael Foster , Jose Miguel Rojas , Robert M Hierons

We present an extension to the robust phase estimation protocol, which can identify incorrect results that would otherwise lie outside the expected statistical range. Robust phase estimation is increasingly a method of choice for…

We define an extension of predicate logic, called Binding Logic, where variables can be bound in terms and in propositions. We introduce a notion of model for this logic and prove a soundness and completeness theorem for it. This theorem is…

Logic in Computer Science · Computer Science 2023-05-26 Gilles Dowek , Thérèse Hardin , Claude Kirchner

We provide a spectrum of results for the Universal Guard Problem, in which one is to obtain a small set of points ("guards") that are "universal" in their ability to guard any of a set of possible polygonal domains in the plane. We give…

Computational Geometry · Computer Science 2017-03-28 Sándor P. Fekete , Qian Li , Joseph S. B. Mitchell , Christian Scheffer

The advantage of quantum protocols lies in the inherent properties of the shared quantum states. These states are sometimes provided by sources that are not trusted, and therefore need to be verified. Finding secure and efficient quantum…

Quantum Physics · Physics 2025-12-16 Fabian Wiesner , Ziad Chaoui , Diana Kessler , Anna Pappa , Martti Karvonen

Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network's prediction. We consider the problem of verifying safety when running a Bayesian neural network…

Machine Learning · Computer Science 2021-11-08 Mathias Lechner , Đorđe Žikelić , Krishnendu Chatterjee , Thomas A. Henzinger

We provide here a proof theoretic account of constraint programming that attempts to capture the essential ingredients of this programming style. We exemplify it by presenting proof rules for linear constraints over interval domains, and…

Artificial Intelligence · Computer Science 2007-05-23 Krzysztof R. Apt

Quantum metrology is a general term for methods to precisely estimate the value of an unknown parameter by actively using quantum resources. In particular, some classes of entangled states can be used to significantly suppress the…

Quantum Physics · Physics 2015-05-01 Takanori Sugiyama

The goal of ordinal embedding is to represent items as points in a low-dimensional Euclidean space given a set of constraints in the form of distance comparisons like "item $i$ is closer to item $j$ than item $k$". Ordinal constraints like…

Machine Learning · Statistics 2016-06-24 Lalit Jain , Kevin Jamieson , Robert Nowak

Using appropriate notation systems for proofs, cut-reduction can often be rendered feasible on these notations, and explicit bounds can be given. Developing a suitable notation system for Bounded Arithmetic, and applying these bounds, all…

Logic in Computer Science · Computer Science 2007-12-11 Klaus Aehlig , Arnold Beckmann

Many papers proved the security of quantum key distribution (QKD) system, in the asymptotic framework. The degree of the security has not been discussed in the finite coding-length framework, sufficiently. However, to guarantee any…

Quantum Physics · Physics 2009-11-13 Masahito Hayashi

We present a new procedure to infer size bounds for integer programs automatically. Size bounds are important for the deduction of bounds on the runtime complexity or in general, for the resource analysis of programs. We show that our…

Logic in Computer Science · Computer Science 2024-11-19 Nils Lommen , Jürgen Giesl

For a broad class of nonlinear systems, we formulate the problem of guaranteeing safety with optimality under constraints. Specifically, we define controlled safety for differential inclusions with constraints on the states and the inputs.…

Optimization and Control · Mathematics 2022-11-24 Masoumeh Ghanbarpour , Axton Isaly , Ricardo G. Sanfelice , Warren E. Dixon
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