Resolution and the Binary Encoding of Combinatorial Principles

被引:2
作者
Dantchev, Stefan [1 ]
Galesi, Nicola [2 ]
Martin, Barnaby [1 ]
机构
[1] Univ Durham, Dept Comp Sci, Durham, England
[2] Sapienza Univ Roma, Dipartimento Informat, Rome, Italy
来源
34TH COMPUTATIONAL COMPLEXITY CONFERENCE (CCC 2019) | 2019年 / 137卷
关键词
Proof complexity; k-DNF resolution; binary encodings; Clique and Pigeonhole principle; WEAK PIGEONHOLE PRINCIPLE; LOWER BOUNDS; RANDOM FORMULAS; COMPLEXITY GAP; PROOFS; SPACE;
D O I
10.4230/LIPIcs.CCC.2019.6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Res(s) is an extension of Resolution working on s-DNFs. We prove tight n(Omega(k)) lower bounds for the size of refutations of the binary version of the k-Clique Principle in Res(o(log log n)). Our result improves that of Lauria, Pudlak et al. [27] who proved the lower bound for Res(1), i.e. Resolution. The exact complexity of the (unary) k-Clique Principle in Resolution is unknown. To prove the lower bound we do not use any form of the Switching Lemma [35], instead we apply a recursive argument specific for binary encodings. Since for the k-Clique and other principles lower bounds in Resolution for the unary version follow from lower bounds in Res(log n) for their binary version we start a systematic study of the complexity of proofs in Resolution-based systems for families of contradictions given in the binary encoding. We go on to consider the binary version of the weak Pigeonhole Principle Bin-PHPnm for m > n. Using the the same recursive approach we prove the new result that for any delta > 0, Bin-PHPnm requires proofs of size 2(n1-delta) in Res(s) for s = o(log(1/2) n). Our lower bound is almost optimal since for m >= 2(root n log n) there are quasipolynomial size proofs of Bin-PHPnm in Res(log n). Finally we propose a general theory in which to compare the complexity of refuting the binary and unary versions of large classes of combinatorial principles, namely those expressible as first order formulae in Pi(2)-form and with no finite model.
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页数:25
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