Projektbeschreibung
Clevere Algorithmen aktualisieren ihre Ergebnisse
Ein Algorithmus ist eine Liste von Anweisungen, die einen gegebenen Eingangswert in den gewünschten Ausgangswert umwandelt. Dieses Paradigma ist bislang mit Erfolg in Theorie und Praxis angewandt worden, aber es wird dabei die Tatsache übersehen, dass sich die Eingabedaten verändern könnten und dass der Algorithmus jede Aktualisierung so schnell wie möglich verarbeiten muss. Ziel des EU-finanzierten Projekts DynASoAr ist die Konzipierung neuartiger Algorithmen für Szenarien mit dynamischen Eingabedaten. Die mit derartigen Algorithmen verbundene Herausforderung liegt darin, dass das Ergebnis der Berechnung nach jeder Datenänderung auf effiziente Weise zu aktualisieren ist, ohne dass eine kostspielige Neuberechnung ganz von vorn begonnen werden muss.
Ziel
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.
Wissenschaftliches Gebiet
Schlüsselbegriffe
Programm/Programme
Thema/Themen
Finanzierungsplan
ERC-STG - Starting GrantGastgebende Einrichtung
5020 Salzburg
Österreich