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Related papers: Object-Spatial Programming

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Object-oriented programming languages such as Java and Objective C have become popular for implementing agent-based and other object-based simulations since objects in those languages can {\em reflect} (i.e. make runtime queries of an…

Mathematical Software · Computer Science 2008-10-22 Russell K. Standish , Duraid Madina

Solving integer optimization problems with large or widely ranged objective coefficients can lead to numerical instability and increased runtimes. When the problem also involves multiple objectives, the impact of the objective coefficients…

Optimization and Control · Mathematics 2025-12-02 Stephanie Riedmüller , Thorsten Koch

Motivated by algorithmic information theory, the problem of program discovery can help find candidates of underlying generative mechanisms of natural and artificial phenomena. The uncomputability of such inverse problem, however,…

Information Theory · Computer Science 2021-12-29 Vladimir Lemusa , Eduardo Acuña , Víctor Zamora , Francisco Hernandez-Quiroz , Hector Zenil

Operating Systems are built upon a set of abstractions to provide resource management and programming APIs for common functionality, such as synchronization, communication, protection, and I/O. The process abstraction is the bridge across…

Operating Systems · Computer Science 2022-05-26 Rodrigo Siqueira , Nelson Lago , Fabio Kon , Dejan Milojičić

Automatic differentiation plays a prominent role in scientific computing and in modern machine learning, often in the context of powerful programming systems. The relation of the various embodiments of automatic differentiation to the…

Programming Languages · Computer Science 2020-02-04 Martin Abadi , Gordon D. Plotkin

Many variability management techniques rely on sophisticated language extension or tools to support it. While this can provide dedicated syntax and operational mechanism but it struggling practical adaptation for the cost of adapting new…

Programming Languages · Computer Science 2021-09-15 Hiun Kim

We present POAPS, a novel planning system for defining Partially Observable Markov Decision Processes (POMDPs) that abstracts away from POMDP details for the benefit of non-expert practitioners. POAPS includes an expressive adaptive…

Artificial Intelligence · Computer Science 2016-09-01 Christopher H. Lin , Mausam , Daniel S. Weld

As generative Artificial Intelligence (AI) technologies evolve, they offer unprecedented potential to automate and enhance various tasks, including coding. Natural Language-Oriented Programming (NLOP), a vision introduced in this paper,…

Software Engineering · Computer Science 2024-06-11 Amin Beheshti

We present Choral, the first choreographic programming language based on mainstream abstractions. The key idea in Choral is a new notion of data type, which allows for expressing that data is distributed over different roles. We use this…

Programming Languages · Computer Science 2023-10-20 Saverio Giallorenzo , Fabrizio Montesi , Marco Peressotti

A new behavior descriptive entity type called spec is proposed, which combines the traditional interface with test rules and test cases, to completely specify the desired behavior of each method, and to enforce the behavior-wise correctness…

Programming Languages · Computer Science 2014-08-21 Chengpu Wang

Spatial understanding is a fundamental cornerstone of human-level intelligence. Nonetheless, current research predominantly focuses on domain-specific data production, leaving a critical void: the absence of a principled, open-source engine…

Answer Set Programming (ASP) is an increasingly popular framework for declarative programming that admits the description of problems by means of rules and constraints that form a disjunctive logic program. In particular, many AI problems…

Computational Complexity · Computer Science 2014-03-07 Johannes Klaus Fichte , Stefan Szeider

We propose relational linear programming, a simple framework for combing linear programs (LPs) and logic programs. A relational linear program (RLP) is a declarative LP template defining the objective and the constraints through the logical…

Artificial Intelligence · Computer Science 2014-10-14 Kristian Kersting , Martin Mladenov , Pavel Tokmakov

Epistemic Logic Programs (ELPs), extend Answer Set Programming (ASP) with epistemic operators. The semantics of such programs is provided in terms of world views, which are sets of belief sets, i.e., syntactically, sets of sets of atoms.…

Artificial Intelligence · Computer Science 2024-11-20 Stefania Costantini , Andrea Formisano

Human visual reasoning is characterized by an ability to identify abstract patterns from only a small number of examples, and to systematically generalize those patterns to novel inputs. This capacity depends in large part on our ability to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Taylor W. Webb , Shanka Subhra Mondal , Jonathan D. Cohen

Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explicit token-level generation, an increasing body of work shows that many critical internal…

One the major challenges in undergraduate computing programs is the learning of object-oriented programming (OOP). This paradigm has a variety of concepts with an abstraction level usually high for most beginners, even the ones who already…

Programming languages are embracing both functional and object-oriented paradigms. A key difference between the two paradigms is the way of achieving data abstraction. That is, how to organize data with associated operations. There are…

Programming Languages · Computer Science 2022-04-25 Weixin Zhang , Cristina David , Meng Wang

Context-Oriented Programming (COP) is a programming paradigm to encourage modularization of context-dependent software. Key features of COP are layers---modules to describe context-dependent behavioral variations of a software system---and…

Programming Languages · Computer Science 2019-09-04 Hiroaki Inoue , Atsushi Igarashi

Space-Time Projection (STP) is introduced as a data-driven forecasting approach for high-dimensional and time-resolved data. The method computes extended space-time proper orthogonal modes from training data spanning a prediction horizon…

Machine Learning · Computer Science 2025-04-01 Oliver T. Schmidt
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