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arXiv 1002.4676cs.CC
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用Pebbling和Branching程序解决树求值问题

Pebbling and Branching Programs Solving the Tree Evaluation Problem

Dustin Wehr

摘要:

我们研究与树评估问题相关的受限计算模型。在早期的工作中,TEP被引入作为分离L和LogDCFL的(* 非常 *)长期目标的简单候选者。该问题的输入是一个高度为h的有根平衡二叉树,其内部节点用[k] = {1,.,k}(每一个简单地给出为[k]的k^2个元素的列表),并且其叶子被标记为[k]的元素。每个节点在[k]中获得一个值,该值等于其应用于其子节点值的二元函数,输出是根节点的值。第一个限制计算模型,称为分数卵石,是图上黑/白卵石游戏的推广,并且以自然的方式从寻找求解TEP的非确定性分支程序(BP)的大小的良好上界中产生-对于任何固定的h,如果高度h的二叉树具有至多p的分数卵石成本,然后有大小为O(k^p)的非确定性BP求解高度h TEP。我们证明了一个下界的分数卵石成本的d-元树,是紧内的一个附加常数为每个固定的d。我们研究的第二个限制计算模型是对(非)确定性BP求解TEP-Thrifty BP的语义限制。确定性(非确定性)节俭BP足以实现用于TEP的最佳已知算法,基于黑色(分别为分数)卵石。在早期的工作中,对于每个固定的h,证明了确定性节俭BP的大小的下限对于足够大的k是紧的。我们给出了一个替代的证明,实现了所有k相同的界限。我们证明了同样的界在一个较少限制的模型中仍然成立,并且对于模型上逐渐较弱的限制,可以得到逐渐较弱的下界。

英文摘要:

We study restricted computation models related to the Tree Evaluation Problem}. The TEP was introduced in earlier work as a simple candidate for the (*very*) long term goal of separating L and LogDCFL. The input to the problem is a rooted, balanced binary tree of height h, whose internal nodes are labeled with binary functions on [k] = {1,...,k} (each given simply as a list of k^2 elements of [k]), and whose leaves are labeled with elements of [k]. Each node obtains a value in [k] equal to its binary function applied to the values of its children, and the output is the value of the root. The first restricted computation model, called Fractional Pebbling, is a generalization of the black/white pebbling game on graphs, and arises in a natural way from the search for good upper bounds on the size of nondeterministic branching programs (BPs) solving the TEP - for any fixed h, if the binary tree of height h has fractional pebbling cost at most p, then there are nondeterministic BPs of size O(k^p) solving the height h TEP. We prove a lower bound on the fractional pebbling cost of d-ary trees that is tight to within an additive constant for each fixed d. The second restricted computation model we study is a semantic restriction on (non)deterministic BPs solving the TEP - Thrifty BPs. Deterministic (resp. nondeterministic) thrifty BPs suffice to implement the best known algorithms for the TEP, based on black (resp. fractional) pebbling. In earlier work, for each fixed h a lower bound on the size of deterministic thrifty BPs was proved that is tight for sufficiently large k. We give an alternative proof that achieves the same bound for all k. We show the same bound still holds in a less-restricted model, and also that gradually weaker lower bounds can be obtained for gradually weaker restrictions on the model.

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