Advice Complexity of Priority Algorithms

被引:3
|
作者
Borodin, Allan [1 ]
Boyar, Joan [2 ]
Larsen, Kim S. [2 ]
Pankratov, Denis [3 ]
机构
[1] Univ Toronto, Dept Comp Sci, Toronto, ON, Canada
[2] Univ Southern Denmark, Dept Math & Comp Sci, Odense, Denmark
[3] Concordia Univ, Dept Comp Sci & Software Engn, Montreal, PQ, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Priority algorithms; Advice complexity; Greedy algorithms; Optimization problems; GREEDY ALGORITHMS;
D O I
10.1007/s00224-019-09955-7
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The priority model of "greedy-like" algorithms was introduced by Borodin, Nielsen, and Rackoff in 2002. We augment this model by allowing priority algorithms to have access to advice, i.e., side information precomputed by an all-powerful oracle. Obtaining lower bounds in the priority model without advice can be challenging and may involve intricate adversary arguments. Since the priority model with advice is even more powerful, obtaining lower bounds presents additional difficulties. We sidestep these difficulties by developing a general framework of reductions which makes lower bound proofs relatively straightforward and routine. We start by introducing the Pair Matching problem, for which we are able to prove strong lower bounds in the priority model with advice. We develop a template for constructing a reduction from Pair Matching to other problems in the priority model with advice - this part is technically challenging since the reduction needs to define a valid priority function for Pair Matching while respecting the priority function for the other problem. Finally, we apply the template to obtain lower bounds for a number of standard discrete optimization problems.
引用
收藏
页码:593 / 625
页数:33
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