Measuring the problem-relevant information in input
Stefan Dobrev, Rastislav Královič, Dana Pardubská (2009)
RAIRO - Theoretical Informatics and Applications
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We propose a new way of characterizing the complexity of online problems. Instead of measuring the degradation of the output quality caused by the ignorance of the future we choose to quantify the amount of additional global information needed for an online algorithm to solve the problem optimally. In our model, the algorithm cooperates with an oracle that can see the whole input. We define the advice complexity of the problem to be the minimal number of bits (normalized per input request,...