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This paper presents several new tractability results for planning based on macros. We describe an algorithm that optimally solves planning problems in a class that we call inverted tree reducible, and is provably tractable for several…

Artificial Intelligence · Computer Science 2014-01-16 Anders Jonsson

In this paper, we propose the distributed tree kernels (DTK) as a novel method to reduce time and space complexity of tree kernels. Using a linear complexity algorithm to compute vectors for trees, we embed feature spaces of tree fragments…

Machine Learning · Computer Science 2012-06-22 Fabio Massimo Zanzotto , Lorenzo Dell'Arciprete

Traditional Turing machines are semantically poor, they only concern the syntactic manipulation of symbols, discarding the mathematical semantics behind the symbols. This semantic deficiency is considered the root cause of the three major…

Computational Complexity · Computer Science 2026-04-21 Bojin Zheng , Jingwen Zheng , Weiwu Wang

We present two restricted versions of one-tape Turing machines. Both characterize the class of context-free languages. In the first version, proposed by Hibbard in 1967 and called limited automata, each tape cell can be rewritten only in…

Formal Languages and Automata Theory · Computer Science 2015-07-31 Giovanni Pighizzini

A Turing machine with faults, failures and recovery (TMF) is described. TMF is (weakly) non-deterministic Turing machine consisting of five semi-infinite tapes (Master Tape, Synchro Tape, Backup Tape, Backup Synchro Tape, User Tape) and…

Logic in Computer Science · Computer Science 2007-05-23 Alex Vinokur

We introduce and investigate forgetting 1-limited automata, which are single-tape Turing machines that, when visiting a cell for the first time, replace the input symbol in it by a fixed symbol, so forgetting the original contents. These…

Formal Languages and Automata Theory · Computer Science 2023-09-19 Giovanni Pighizzini , Luca Prigioniero

The input/output complexity, which is the complexity of data exchange between the main memory and the external memory, has been elaborately studied by a lot of former researchers. However, the existing works failed to consider the…

Computational Complexity · Computer Science 2022-08-23 Hengzhao Ma , Jianzhong Li , Xiangyu Gao , Tianpeng Gao

While there exist many methods in machine learning for comparison of letter string data, most are better equipped to handle strings that represent natural language, and their performance will not hold up when presented with strings that…

Artificial Intelligence · Computer Science 2021-02-15 Reza Shahbazi

Clift and Murfet (2019) introduced a naive Bayesian smooth relaxation of Turing machines motivated by work in differential linear logic; this was subsequently used to endow spaces of program codes of bounded length with a smooth manifold…

Logic · Mathematics 2021-06-03 Adrian K. Xu

This paper attempts a more formal approach to the legibility of text based programming languages, presenting, with proof, minimum possible ways of representing structure in text interleaved with information. This presumes that a minimalist…

Programming Languages · Computer Science 2017-06-06 Brenton Chapin

Many common sequential data sources, such as source code and natural language, have a natural tree-structured representation. These trees can be generated by fitting a sequence to a grammar, yielding a hierarchical ordering of the tokens in…

Machine Learning · Computer Science 2019-08-02 Jacob Harer , Chris Reale , Peter Chin

Tree-based methods are popular machine learning techniques used in various fields. In this work, we review their foundations and a general framework the importance sampled learning ensemble (ISLE) that accelerates their fitting process.…

Machine Learning · Statistics 2022-05-02 Yinuo Zeng

Justification theory is an abstract unifying formalism that captures semantics of various non-monotonic logics. One intriguing problem that has received significant attention is the consistency problem: under which conditions are…

Artificial Intelligence · Computer Science 2022-08-08 Simon Marynissen , Bart Bogaerts

The preceding paper constructed tangle machines as diagrammatic models, and illustrated their utility with a number of examples. The information content of a tangle machine is contained in characteristic quantities associated to equivalence…

Information Theory · Computer Science 2014-04-11 Avishy Y. Carmi , Daniel Moskovich

Simulations of weighted tree automata (wta) are considered. It is shown how such simulations can be decomposed into simpler functional and dual functional simulations also called forward and backward simulations. In addition, it is shown in…

Formal Languages and Automata Theory · Computer Science 2015-05-18 Zoltán Ésik , Andreas Maletti

We show that alternating Turing machines, with a novel and natural definition of acceptance, accept precisely the inductive (Pi-1-1) languages. Total alternating machines, that either accept or reject each input, accept precisely the…

Logic in Computer Science · Computer Science 2015-07-01 Daniel M Leivant

This paper describes a new and purely functional implementation technique of binary heaps. A binary heap is a tree-based data structure that implements priority queue operations (insert, remove, minimum/maximum) and guarantees at worst…

Data Structures and Algorithms · Computer Science 2013-12-18 Vladimir Kostyukov

Applications in many domains are based on a series of traversals of tree structures, and fusing these traversals together to reduce the total number of passes over the tree is a common, important optimization technique. In applications such…

Programming Languages · Computer Science 2019-04-22 Laith Sakka , Kirshanthan Sundararajah , Ryan R. Newton , Milind Kulkarni

The notion of transducer integer sequences is considered through a series of examples. By definition, transducer integer sequences are integer sequences produced, under a suitable interpretation, by finite automata encoding tree morphisms…

Combinatorics · Mathematics 2007-05-23 Zoran Sunic

Dynamic trees are mixtures of tree structured belief networks. They solve some of the problems of fixed tree networks at the cost of making exact inference intractable. For this reason approximate methods such as sampling or mean field…

Machine Learning · Computer Science 2013-01-18 Amos J. Storkey