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In the present paper, several types of efficiency conditions are established for vector optimization problems with cone constraints affected by uncertainty, but with no information of stochastic nature about the uncertain data. Following a…

Optimization and Control · Mathematics 2021-02-01 Amos Uderzo

Extreme edge computing (EEC) refers to the endmost part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer computational…

Networking and Internet Architecture · Computer Science 2022-08-12 Mhd Saria Allahham , Amr Mohamed , Aiman Erbad , Hossam Hassanein

In this note, we provide complexity characterizations of model checking multi-pushdown systems. Multi-pushdown systems model recursive concurrent programs in which any sequential process has a finite control. We consider three standard…

Logic in Computer Science · Computer Science 2012-12-10 Kshitij Bansal , Stéphane Demri

Weighted A* (wA*) is a widely used algorithm for rapidly, but suboptimally, solving planning and search problems. The cost of the solution it produces is guaranteed to be at most W times the optimal solution cost, where W is the weight wA*…

Artificial Intelligence · Computer Science 2023-05-29 Robert C. Holte , Ruben Majadas , Alberto Pozanco , Daniel Borrajo

Solving problems through tool use under explicit constraints constitutes a highly challenging yet unavoidable scenario for large language models (LLMs), requiring capabilities such as function calling, instruction following, and…

Computation and Language · Computer Science 2026-03-17 Junjie Ye , Guoqiang Zhang , Wenjie Fu , Tao Gui , Qi Zhang , Xuanjing Huang

We investigate the mathematical properties of event bound functions as they are used in the worst-case response time analysis and utilization tests. We figure out the differences and similarities between the two approaches. Based on this…

Operating Systems · Computer Science 2020-07-24 Frank Slomka , Mohammadreza Sadeghi

Optimization of complex functions, such as the output of computer simulators, is a difficult task that has received much attention in the literature. A less studied problem is that of optimization under unknown constraints, i.e., when the…

Methodology · Statistics 2010-07-06 Robert B. Gramacy , Herbert K. H. Lee

Prior work on automatic control synthesis for cyber-physical systems under logical constraints has primarily focused on environmental disturbances or modeling uncertainties, however, the impact of deliberate and malicious attacks has been…

Systems and Control · Electrical Eng. & Systems 2019-07-25 Luyao Niu , Andrew Clark

Time-distributed Optimization (TDO) is an approach for reducing the computational burden of Model Predictive Control (MPC). When using TDO, optimization iterations are distributed over time by maintaining a running solution estimate and…

Optimization and Control · Mathematics 2021-02-25 Dominic Liao-McPherson , Terrence Skibik , Jordan Leung , Ilya Kolmanovsky , Marco M. Nicotra

Web service applications are distributed processes that are composed of dynamically bounded services. In our previous work [15], we have described a framework for performing runtime monitoring of web service against behavioural correctness…

Software Engineering · Computer Science 2010-09-21 Jocelyn Simmonds , Shoham Ben-David , Marsha Chechik

This paper introduces a novel approach to the optimal control of linear discrete-time systems subject to bounded disturbances. Our approach is based on the newly established duality between ellipsoidal approximations of reachable and hardly…

Systems and Control · Electrical Eng. & Systems 2024-09-20 Egor Dogadin , Alexey Peregudin , Dmitriy Shirokih

Optimization problems with uncertain black-box constraints, modeled by warped Gaussian processes, have recently been considered in the Bayesian optimization setting. This work introduces a new class of constraints in which the same…

Optimization and Control · Mathematics 2020-06-16 Johannes Wiebe , Inês Cecílio , Jonathan Dunlop , Ruth Misener

Human behavior is conditioned by codes and norms that constrain action. Rules, ``manners,'' laws, and moral imperatives are examples of classes of constraints that govern human behavior. These systems of constraints are "messy:" individual…

Artificial Intelligence · Computer Science 2023-06-16 Robert E. Wray , Steven J. Jones , John E. Laird

Optimization - minimization or maximization - in the lattice of subsets is a frequent operation in Artificial Intelligence tasks. Examples are subset-minimal model-based diagnosis, nonmonotonic reasoning by means of circumscription, or…

Artificial Intelligence · Computer Science 2016-12-23 Wolfgang Faber , Mauro Vallati , Federico Cerutti , Massimiliano Giacomin

The execution time of programs is a key element in many areas of computer science, mainly those where achieving good performance (e.g., scheduling in cloud computing) or a predictable one (e.g., meeting deadlines in embedded systems) is the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-13 Matheus Henrique Junqueira Saldanha

The safe operation of an autonomous system is a complex endeavor, one pivotal element being its decision-making. Decision-making logic can formally be analyzed using model checking or other formal verification approaches. Yet, the…

Multiagent Systems · Computer Science 2023-10-05 Jan Vermaelen , Tom Holvoet

While there are many approaches for automatically proving termination of term rewrite systems, up to now there exist only few techniques to disprove their termination automatically. Almost all of these techniques try to find loops, where…

Logic in Computer Science · Computer Science 2010-12-30 René Thiemann , Christian Sternagel , Jürgen Giesl , Peter Schneider-Kamp

Tracers provide users with useful information about program executions. In this article, we propose a ``tracer driver''. From a single tracer, it provides a powerful front-end enabling multiple dynamic analysis tools to be easily…

Software Engineering · Computer Science 2008-12-18 Ludovic Langevine , Mireille Ducasse

Neural networks (NNs) are now routinely implemented on systems that must operate in uncertain environments, but the tools for formally analyzing how this uncertainty propagates to NN outputs are not yet commonplace. Computing tight bounds…

Machine Learning · Computer Science 2020-12-08 Michael Everett , Golnaz Habibi , Jonathan P. How

As the complexity of control systems increases, the need for systematic methods to guarantee their efficacy grows as well. However, direct testing of these systems is oftentimes costly, difficult, or impractical. As a result, the test and…

Systems and Control · Electrical Eng. & Systems 2021-09-10 Prithvi Akella , Ugo Rosolia , Aaron D. Ames