Probabilistic Continuous Constraint Satisfaction Problems

Carvalho, Elsa; Cruz, Jorge; Barahona, Pedro

doi:10.1109/ictai.2008.75

Cited by 7 publications

(2 citation statements)

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“…(See Section VII below.) Interest in speeding up the mixing time by using computational probabilistic reasoning [26] more broadly has led to a variety of schemes that introduce adaptivity into the classical method to improve performance. However, progress has been limited to distributions of a particular structure.…”

Section: Background: Classical Monte Carlomentioning

confidence: 99%

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

Intallura¹,

Korpas²,

Chakraborty³

et al. 2023

Preprint

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Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought to be estimated. In this paper, we survey the literature for implementing Monte Carlo procedures using quantum circuits, focusing on the potential to obtain a quantum advantage in the computational speed of these procedures. We revisit the quantum algorithms that could replace classical Monte Carlo and then consider both the existing quantum algorithms and the potential quantum realizations that include adaptive enhancements as alternatives to the classical procedure.

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Section: Background: Classical Monte Carlomentioning

confidence: 99%

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond

Intallura¹,

Korpas²,

Chakraborty³

et al. 2023

Preprint

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“…To formalize the probabilistic constraint paradigm, a generic description and some preliminary results were published in [23], while a more formal characterization was published in [24].…”

Section: Probabilistic Constraint Programmingmentioning

confidence: 99%

Probabilistic constraint reasoning

Carvalho¹

2015

Constraints

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perpétuo e sem limites geográficos, de arquivar e publicar esta dissertação através de exemplares impressos reproduzidos em papel ou de forma digital, ou por qualquer outro meio conhecido ou que venha a ser inventado, e de a divulgar através de repositórios científicos e de admitir a sua cópia e distribuição com objectivos educacionais ou de investigação, não comerciais, desde que seja dado crédito ao autor e editor.For Laura with love.My endless source of inspiration with her tender heart and ingenious mind. AcknowledgementsFor me, writing this thesis was like a long, long journey, with many ups and downs. In every step of the way I faced challenges that made me grow as a researcher and as a person. But the journey is coming to an end and is now time to remember and be grateful to those who crossed my path and helped me to achieve my goal in many different ways. Neste trabalho desenvolvemos um paradigma de restrições em domínios contínuos que associa um espaço probabilísticoàs variáveis do problema, permitindo efectuar raciocínio probabilístico. Tal raciocínio baseia-se na avaliação de informação probabilística que requer a computação de integrais multidimensionais em regiões possivelmente não lineares. São desenvolvidos algoritmos capazes de avaliar essa informação, usando técnicas de integração seguras ou aproximadas e dependendo de métodos de programação por restrições em domínios contínuos para obter coberturas da região de integração.A plataforma probabilística de restrições em domínios contínuosé adequada para suporteà decisão em problemas não lineares em domínios contínuos, com incerteza. A sua aplicabilidadeé ilustrada em problemas inversos e problemas de fiabilidade, que são duas classes distintas de problemas de engenharia, representativas do tipo de raciocínio com incerteza requerido pelos decisores.

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