Online computation with advice

Online Computation with Advice

We consider a model for online computation in which the online algorithm receives, together with each request, some information regarding the future, referred to as advice. The advice provided to the online algorithm may allow an improvement in its performance, compared to the classical model of complete lack of information regarding the future. We are interested in the impact of such advice on...

Advice and Randomization in Online Computation

Online computation is both of theoretical interest and practical relevance as numerous computational problems require a model in which algorithms do not know the whole input at every time step during runtime. The established measurement for the output quality of these online algorithms is the so-called competitive analysis, introduced by Sleator and Tarjan in 1985. Similar to the decrease in ac...

Computation with Advice

Computation with advice is suggested as generalization of both computation with discrete advice and Type-2 Nondeterminism. Several embodiments of the generic concept are discussed, and the close connection to Weihrauch reducibility is pointed out. As a novel concept, computability with random advice is studied; which corresponds to correct solutions being guessable with positive probability. In...

Online Algorithms with Advice⋆

In online problems, the input forms a finite sequence of requests. Each request must be processed, i. e., a partial output has to be computed only depending on the requests having arrived so far, and it is not allowed to change this partial output subsequently. The aim of an online algorithm is to produce a sequence of partial outputs that optimizes some global measure. The most frequently used...

Online Algorithms with Advice