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Aggregation functions are widely used in answer set programming for representing and reasoning on knowledge involving sets of objects collectively. Current implementations simplify the structure of programs in order to optimize the overall…

Artificial Intelligence · Computer Science 2020-02-19 Mario Alviano , Wolfgang Faber , Martin Gebser

Humans develop their grammars by making structural generalizations from finite input. We ask how filler-gap dependencies, which share a structural generalization despite diverse surface forms, might arise from the input. We explicitly…

Computation and Language · Computer Science 2024-10-25 Katherine Howitt , Sathvik Nair , Allison Dods , Robert Melvin Hopkins

Large Language Models offer new opportunities to devise automated implementation generation methods that can tackle problem solving activities beyond traditional methods, which require algorithmic specifications and can use only static…

Computation and Language · Computer Science 2025-01-06 Hashmath Shaik , Alex Doboli

We propose a presentation of classical propositional tableaux elaborated by application of methods that are noteworthy in program design, namely program derivation with separation of concerns. We start by deriving from a straightforward…

Computers and Society · Computer Science 2015-07-15 Juan Michelini , Alvaro Tasistro

Reflective systems allow their own structures to be altered from within. Here we are concerned with a style of reflection, called linguistic reflection, which is the ability of a running program to generate new program fragments and to…

Programming Languages · Computer Science 2007-05-23 G. N. C. Kirby , R. Morrison , D. W. Stemple

Probabilistic programming is considered as a framework, in which basic components of cognitive architectures can be represented in unified and elegant fashion. At the same time, necessity of adopting some component of cognitive…

Artificial Intelligence · Computer Science 2016-05-05 Alexey Potapov

We present module theory and linear maps as a powerful generalised and computationally efficient framework for the relational data model, which underpins today's relational database systems. Based on universal constructions of modules we…

Programming Languages · Computer Science 2022-07-05 Fritz Henglein , Robin Kaarsgaard , Mikkel Kragh Mathiesen

Graph data management (also called NoSQL) has revealed beneficial characteristics in terms of flexibility and scalability by differently balancing between query expressivity and schema flexibility. This peculiar advantage has resulted into…

Databases · Computer Science 2019-09-10 Harsh Thakkar , Dharmen Punjani , Soeren Auer , Maria-Esther Vidal

Qualification has been recently introduced as a generalization of uncertainty in the field of Logic Programming. In this report we investigate a more expressive language for First-Order Functional Logic Programming with Constraints and…

Programming Languages · Computer Science 2011-01-12 Rafael Caballero , Mario Rodríguez-Artalejo , Carlos A. Romero-Díaz

In this paper we examine how concurrency has been embodied in mainstream programming languages. In particular, we rely on the evolutionary talking borrowed from biology to discuss major historical landmarks and crucial concepts that shaped…

Programming Languages · Computer Science 2015-07-29 Silvia Crafa

We introduce and implement a cognitively plausible model for learning from generic language, statements that express generalizations about members of a category and are an important aspect of concept development in language acquisition…

Computation and Language · Computer Science 2021-05-10 Deniz Beser , Joe Cecil , Marjorie Freedman , Jacob Lichtefeld , Mitch Marcus , Sarah Payne , Charles Yang

Recent strides in interpretable machine learning (ML) research reveal that models exploit undesirable patterns in the data to make predictions, which potentially causes harms in deployment. However, it is unclear how we can fix these…

To solve hard problems, AI relies on a variety of disciplines such as logic, probabilistic reasoning, machine learning and mathematical programming. Although it is widely accepted that solving real-world problems requires an integration…

Artificial Intelligence · Computer Science 2020-01-14 Vaishak Belle , Luc De Raedt

Length generalization refers to the ability to extrapolate from short training sequences to long test sequences and is a challenge for current large language models. While prior work has proposed some architecture or data format changes to…

Machine Learning · Computer Science 2024-07-04 Kaiying Hou , David Brandfonbrener , Sham Kakade , Samy Jelassi , Eran Malach

Objective Caml is a famous dialect of the ML family languages. It is well-known for its performance as a compiled programming language, notably thanks to its incremental generational automatic memory collection. However, for historical…

Programming Languages · Computer Science 2020-06-11 Mathias Bourgoin , Benjamin Canou , Emmanuel Chailloux , Adrien Jonquet , Philippe Wang

Algebraic specifications of data types provide a natural basis for testing data types implementations. In this framework, the conformance relation is based on the satisfaction of axioms. This makes it possible to formally state the…

Programming Languages · Computer Science 2008-12-18 Marie-Claude Gaudel , Pascale Le Gall

This research started with an algebra for reasoning about rely/guarantee concurrency for a shared memory model. The approach taken led to a more abstract algebra of atomic steps, in which atomic steps synchronise (rather than interleave)…

Logic in Computer Science · Computer Science 2022-01-19 Ian J. Hayes , Robert Colvin , Larissa Meinicke , Kirsten Winter , Andrius Velykis

Rewriting is a formalism widely used in computer science and mathematical logic. The classical formalism has been extended, in the context of functional languages, with an order over the rules and, in the context of rewrite based languages,…

Logic in Computer Science · Computer Science 2019-06-12 Horatiu Cirstea , Pierre-Etienne Moreau

Class incremental learning (CIL) trains a network on sequential tasks with separated categories in each task but suffers from catastrophic forgetting, where models quickly lose previously learned knowledge when acquiring new tasks. The…

Machine Learning · Computer Science 2024-11-05 Huiping Zhuang , Yizhu Chen , Di Fang , Run He , Kai Tong , Hongxin Wei , Ziqian Zeng , Cen Chen

Generalized planning is concerned with the characterization and computation of plans that solve many instances at once. In the standard formulation, a generalized plan is a mapping from feature or observation histories into actions,…

Artificial Intelligence · Computer Science 2018-06-15 Blai Bonet , Hector Geffner