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We propose the \textbf{Asterisk Operator} ($\ast$-operator), a novel unified framework for abstract reasoning based on Adjacency-Structured Parallel Propagation (ASPP). The operator formalizes structured reasoning tasks as local, parallel…

Artificial Intelligence · Computer Science 2025-09-18 Zixi Li

In previous work, we proposed a logic-based framework in which computation is the execution of actions in an attempt to make reactive rules of the form if antecedent then consequent true in a canonical model of a logic program determined by…

Artificial Intelligence · Computer Science 2020-02-19 Robert Kowalski , Fariba Sadri

We propose an approach to the semantics of package management which relates it to general event structures, well-known mathematical objects used in the semantics of concurrent, nondeterministic systems. In this approach, the data of a…

Logic in Computer Science · Computer Science 2021-07-06 Gershom Bazerman

Dynamic programming (DP) is a cornerstone of combinatorial optimization, yet its inherently sequential structure has long limited its scalability in scenario-based stochastic programming (SP). This paper introduces a GPU-accelerated…

Optimization and Control · Mathematics 2025-11-25 Jingyi Zhao , Linxin Yang , Haohua Zhang , Tian Ding

Formal verification of software and compilers has been used to rule out large classes of security-critical issues, but risk of unintentional information leakage has received much less consideration. It is a key requirement for formal…

Programming Languages · Computer Science 2025-04-23 Owen Conoly , Andres Erbsen , Adam Chlipala

Zero-shot capabilities of large language models make them powerful tools for solving a range of tasks without explicit training. It remains unclear, however, how these models achieve such performance, or why they can zero-shot some tasks…

Computation and Language · Computer Science 2024-12-11 Alan Sun , Ethan Sun , Warren Shepard

Students find their first course in Formal Languages and Automata Theory challenging. In addition to the development of formal arguments, most students struggle to understand nondeterministic computation models. In part, the struggle stems…

Programming Languages · Computer Science 2023-10-24 Oliwia Kempinski , Marco T. Morazán

This work presents the use of graph learning for the prediction of multi-step experimental outcomes for applications across experimental research, including material science, chemistry, and biology. The viability of geometric learning for…

Machine Learning · Computer Science 2024-08-13 Amanda A. Volk , Robert W. Epps , Jeffrey G. Ethier , Luke A. Baldwin

This tutorial gives an advanced introduction to string diagrams and graph languages for higher-order computation. The subject matter develops in a principled way, starting from the two dimensional syntax of key categorical concepts such as…

Logic in Computer Science · Computer Science 2024-12-05 Dan Ghica , Fabio Zanasi

Describing systems in terms of choices and their resulting costs and rewards offers the promise of freeing algorithm designers and programmers from specifying how those choices should be made; in implementations, the choices can be realized…

Logic in Computer Science · Computer Science 2024-02-14 Martin Abadi , Gordon Plotkin

The functionality of a graph $G$ is the minimum number $k$ such that in every induced subgraph of $G$ there exists a vertex whose neighbourhood is uniquely determined by the neighborhoods of at most $k$ other vertices in the subgraph. The…

Combinatorics · Mathematics 2024-12-30 John Sylvester , Viktor Zamaraev , Maksim Zhukovskii

We present some applications of intermediate logics in the field of Answer Set Programming (ASP). A brief, but comprehensive introduction to the answer set semantics, intuitionistic and other intermediate logics is given. Some equivalence…

Logic in Computer Science · Computer Science 2007-05-23 Mauricio Osorio , Juan Antonio Navarro , Jose Arrazola

Large pre-trained language models perform remarkably well on tasks that can be done "in one pass", such as generating realistic text or synthesizing computer programs. However, they struggle with tasks that require unbounded multi-step…

We introduce a new type of shift dynamics as an extended model of symbolic dynamics, and investigate the characteristics of shift spaces from the viewpoints of both dynamics and computation. This shift dynamics is called a functional shift…

Chaotic Dynamics · Physics 2009-11-10 Jun Namikawa , Takashi Hashimoto

With the growing need for online and iterative graph processing, software systems that continuously process large-scale graphs become widely deployed. With optimizations inherent as part of their design, these systems are complex, and have…

Programming Languages · Computer Science 2020-06-15 Philip Dexter , Yu David Liu , Kenneth Chiu

Predictive models are fundamental to engineering reliable software systems. However, designing conservative, computable approximations for the behavior of programs (static analyses) remains a difficult and error-prone process for modern…

Programming Languages · Computer Science 2011-05-10 David Van Horn , Matthew Might

In logic programming, dynamic scheduling refers to a situation where the selection of the atom in each resolution (computation) step is determined at runtime, as opposed to a fixed selection rule such as the left-to-right one of Prolog.…

Logic in Computer Science · Computer Science 2007-05-23 Annalisa Bossi , Sandro Etalle , Sabina Rossi , Jan-Georg Smaus

Compensating CSP (cCSP) is a language defined to model long running business transactions within the framework of standard CSP process algebra. In earlier work, we have defined both traces and operational semantics of the language. We have…

Logic in Computer Science · Computer Science 2010-01-21 Shamim H. Ripon , Michael Butler

UML activity diagrams have become an established notation to model control and data ow on various levels of abstraction, ranging from fine-grained descriptions of algorithms to high-level workflow models in business applications. A formal…

Software Engineering · Computer Science 2014-09-09 Hans Grönninger , Dirk Reiß , Bernhard Rumpe

Graph neural networks form a class of deep learning architectures specifically designed to work with graph-structured data. As such, they share the inherent limitations and problems of deep learning, especially regarding the issues of…

Formal Languages and Automata Theory · Computer Science 2024-10-16 Matteo Belenchia , Flavio Corradini , Michela Quadrini , Michele Loreti