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Dynamic Algorithms Against Strong Adversaries

From a procedural viewpoint, an algorithm is a list of instructions that transforms a given input into the desired output. While this paradigm has been successfully applied in theory and practice, it completely neglects the fact t... ver más

31/08/2026

PLUS

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

PARISLODRONUNIVERSITAT SALZBURG No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-09-01

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2020-STG: ERC STARTING GRANTS

I+D

Cerrada hace 5 años

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2 Participantes

PLUS

1.50M€ | Lider

PEOPLETEL

847.98K€ | Participante

Últimas noticias

29-11-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

29-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 2 concesiones

29-11-2024: CMVAMADRID En las últimas 48 horas el Organismo CMVAMADRID ha otorgado 37 concesiones

Duración del proyecto: 71 meses Fecha Inicio: 2020-09-01
Fecha Fin: 2026-08-31

Líder del proyecto

PARISLODRONUNIVERSITAT SALZBURG

TRL 4-5

Presupuesto del proyecto 1M€

Descripción del proyecto From a procedural viewpoint, an algorithm is a list of instructions that transforms a given input into the desired output. While this paradigm has been successfully applied in theory and practice, it completely neglects the fact that in many scenarios the input is not given to the algorithm in its entirety at the beginning and might undergo changes that the algorithm needs to react to. Formally, such a situation can be modeled as a game between an adversary creating the sequence of updates to the input and an algorithm that tries to process each of these updates as fast as possible. Researchers have studied such dynamic problems with increasing interest in the past years. However, many state-of-the-art solutions suffer from at least one of the following drawbacks: (1) Many dynamic algorithms are randomized and assume that the sequence of updates is independent of the random choices made by the algorithm. This is not justified in situations where the next update to the input naturally depends on the previous outputs of the algorithm. (2) Many dynamic algorithms achieve amortized running time guarantees where the stated guarantee on processing each update only holds on average and occasionally significantly more time might be needed. This is insufficient for real-time systems requiring hard worst-case guarantees. The goal of this project is to design dynamic algorithms free from these two shortcomings. Formally, this amounts to giving the adversary the following additional powers: (1) adapting its update sequence to the outputs of the algorithm and (2) discarding the algorithm if some update is not processed in time. While isolated results in this direction exist, with some of them obtained by the PI, the unique feature of this project is the systematic study of these stronger adversarial models for otherwise well-studied dynamic problems. Our results will facilitate the use of dynamic algorithms in both real-world applications and in the design of static algorithms.

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