H2020Индивидуална стипендия2018–2021

InfCSP · Descriptive Complexity of Infinite Domain Constraint Satisfaction Problems

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период
2018-07-01 → 2021-04-29
Финансиране от ЕС
195 455 €
Участници
1
Схема
MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Задачи за удовлетворяване на ограничения с безкраен брой стойности, като например разписания или системи от уравнения, се анализират чрез математическата логика и симетрията. Това помага за по-доброто разбиране на сложността на изчисленията в изкуствения интелект и компютърната биология.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Descriptive Complexity of Infinite Domain Constraint Satisfaction Problems

The constraint satisfaction problem is a computational problem where the input consists of a set of variables and a set of constraints, and the goal is to decide whether there exists an assignment of values to the variables satisfying all the constraints. This simple framework captures many computational problems such as satisfiability, graph colouring or solving systems of equations. The unified formulation allows for analysing such problems globally, instead of studying each problem in isolation. Intense efforts to understand the complexity of constraint satisfaction problems with a finite set of values culminated recently in the confirmation of the famous Dichotomy Conjecture - it has been shown that every problem of this kind is either NP-complete or solvable in polynomial time. However, for many problems which appear naturally in different areas of computer science, such as combinatorial optimisation, artificial intelligence, scheduling and computational biology, the scenario where the set of possible values is finite is too restricted. The overall objective of this project was to exploit the consequences of symmetries to understand the power of logic-based approaches to the infinite domain constraint satisfaction problem - a version of the constraint satisfaction problem where the set of possible values is infinite. The project, taking place at the interface of mathematics and computer science, advanced the research on symmetric computation and strengthened collaborations between the University of Cambridge and other world-leading institutions in the field.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

The constraint satisfaction problem (CSP) is a computational problem where the instance consists of a finite set of variables and a finite set of constraints, and the goal is to decide if there is a mapping from the variables to elements of some fixed domain of values satisfying all the constraints. Such problems are ubiquitous in different areas of computer science, including artificial intelligence, scheduling, computational linguistics, computational biology, and combinatorial optimisation. InfCSP will use mathematical tools to study the descriptive complexity of infinite domain constraint satisfaction problems.The main purpose of InfCSP is to understand the power of generic logic-based algorithms for CSPs with infinite domains of values. More precisely, we will analyse the class of CSPs parametrised by the type of constraints allowed in the instance in order to determine for which problems in this class the set of YES instances can be captured by a logical formula. The logics of interest will be Datalog and the first-order logic extended by a fixed-point operator, widely studied in the context of constraint satisfaction. The classifications will be obtained using methods from descriptive complexity, universal algebra and model theory. InfCSP will constitute a major step forward in understanding which infinite domain CSPs can be solved in polynomial time and developing new universal-algebraic tools for infinite domain CSP.

Оригинален текст от CORDIS (на английски).

Участници

Връзки

Данни: CORDIS, © Европейски съюз