9 research outputs found

    Generation, Ranking and Unranking of Ordered Trees with Degree Bounds

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    We study the problem of generating, ranking and unranking of unlabeled ordered trees whose nodes have maximum degree of Δ\Delta. This class of trees represents a generalization of chemical trees. A chemical tree is an unlabeled tree in which no node has degree greater than 4. By allowing up to Δ\Delta children for each node of chemical tree instead of 4, we will have a generalization of chemical trees. Here, we introduce a new encoding over an alphabet of size 4 for representing unlabeled ordered trees with maximum degree of Δ\Delta. We use this encoding for generating these trees in A-order with constant average time and O(n) worst case time. Due to the given encoding, with a precomputation of size and time O(n^2) (assuming Δ\Delta is constant), both ranking and unranking algorithms are also designed taking O(n) and O(nlogn) time complexities.Comment: In Proceedings DCM 2015, arXiv:1603.0053

    Generation of Neuronal Trees by a New Three Letters Encoding

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    A neuronal tree is a rooted tree with n leaves whose each internal node has at least two children; this class not only is defined based on the structure of dendrites in neurons, but also refers to phylogenetic trees or evolutionary trees. More precisely, neuronal trees are rooted-multistate phylogenetic trees whose size is defined as the number of leaves. In this paper, a new encoding over an alphabet of size 3 (minimal cardinality) is introduced for representing the neuronal trees with a given number of leaves. This encoding is used for generating neuronal trees with n leaves in A-order with constant average time and O(n) time complexity in the worst case. Also, new ranking and unranking algorithms are presented in time complexity of O(n) and O(n log n), respectively

    Gap terminology and related combinatorial properties for AVL trees and Fibonacci-isomorphic trees

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    We introduce gaps that are edges or external pointers in AVL trees such that the height difference between the subtrees rooted at their two endpoints is equal to 2. Using gaps we prove the Basic-Theorem that illustrates how the size of an AVL tree (and its subtrees) can be represented by a series of powers of 2 of the heights of the gaps, this theorem is the first such simple formula to characterize the number of nodes in an AVL tree. Then, we study the extreme case of AVL trees, the perfectly unbalanced AVL trees, by introducing Fibonacci-isomorphic trees that are isomorphic to Fibonacci trees of the same height and showing that they have the maximum number of gaps in AVL trees. Note that two ordered trees (such as AVL trees) are isomorphic iff there exists a one-to-one correspondence between their nodes that preserves not only adjacency relations in the trees, but also the roots. In the rest of the paper, we study combinatorial properties of Fibonacci-isomorphic trees. (C) 2018 Kalasalingam University. Publishing Services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/)

    New Combinatorial Properties and Algorithms for AVL Trees

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    In this thesis, new properties of AVL trees and a new partitioning of binary search trees named core partitioning scheme are discussed, this scheme is applied to three binary search trees namely AVL trees, weight-balanced trees, and plain binary search trees. We introduce the core partitioning scheme, which maintains a balanced search tree as a dynamic collection of complete balanced binary trees called cores. Using this technique we achieve the same theoretical efficiency of modern cache-oblivious data structures by using classic data structures such as weight-balanced trees or height balanced trees (e.g. AVL trees). We preserve the original topology and algorithms of the given balanced search tree using a simple post-processing with guaranteed performance to completely rebuild the changed cores (possibly all of them) after each update. Using our core partitioning scheme, we simultaneously achieve good memory allocation, space-efficient representation, and cache-obliviousness. We also apply this scheme to arbitrary binary search trees which can be unbalanced and we produce a new data structure, called Cache-Oblivious General Balanced Tree (COG-tree). Using our scheme, searching a key requires O(log_B n) block transfers and O(log n) comparisons in the external-memory and in the cache-oblivious model. These complexities are theoretically efficient. Interestingly, the core partition for weight-balanced trees and COG-tree can be maintained with amortized O(log_B n) block transfers per update, whereas maintaining the core partition for AVL trees requires more than a poly-logarithmic amortized cost. Studying the properties of these trees also lead us to some other new properties of AVL trees and trees with bounded degree, namely, we present and study gaps in AVL trees and we prove Tarjan et al.'s conjecture on the number of rotations in a sequence of deletions and insertions

    Subject index volumes 1–92

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    ICAPS 2012. Proceedings of the third Workshop on the International Planning Competition

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    22nd International Conference on Automated Planning and Scheduling. June 25-29, 2012, Atibaia, Sao Paulo (Brazil). Proceedings of the 3rd the International Planning CompetitionThe Academic Advising Planning Domain / Joshua T. Guerin, Josiah P. Hanna, Libby Ferland, Nicholas Mattei, and Judy Goldsmith. -- Leveraging Classical Planners through Translations / Ronen I. Brafman, Guy Shani, and Ran Taig. -- Advances in BDD Search: Filtering, Partitioning, and Bidirectionally Blind / Stefan Edelkamp, Peter Kissmann, and Álvaro Torralba. -- A Multi-Agent Extension of PDDL3.1 / Daniel L. Kovacs. -- Mining IPC-2011 Results / Isabel Cenamor, TomĂĄs de la Rosa, and Fernando FernĂĄndez. -- How Good is the Performance of the Best Portfolio in IPC-2011? / Sergio Nuñez, Daniel Borrajo, and Carlos Linares LĂłpez. -- “Type Problem in Domain Description!” or, Outsiders’ Suggestions for PDDL Improvement / Robert P. Goldman and Peter KellerEn prens

    LIPIcs, Volume 248, ISAAC 2022, Complete Volume

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    LIPIcs, Volume 248, ISAAC 2022, Complete Volum
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