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检索条件"主题词=Algorithmic complexity"

共 293 条记录，以下是221-230 订阅

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The Best-partitions Problem: How to Build Meaningful Aggregations

The Best-partitions Problem: How to Build Meaningful Aggrega...

引用

12th IEEE/WIC/ACM International Joint Conference on Intelligent Agent Technology (IAT)

作者： Lamarche-Perrin, Robin Demazeau, Yves Vincent, Jean-Marc Univ Grenoble Alpes LIG Grenoble France CNRS LIG F-75700 Paris France

ISBN: (纸本)9781479929023

The design and the debugging of large distributed AI systems require abstraction tools to build tractable macroscopic descriptions. Data aggregation provides such tools by partitioning the system dimensions into aggregated pieces of information. Since this process leads to information losses, the partitions should be chosen with the greatest caution. While the number of possible partitions grows exponentially with the size of the system, this paper proposes an algorithm that exploits exogenous constraints regarding the system semantics in order to find the best partitions in a linear or polynomial time. Two constrained sets of partitions (hierarchical and ordered) are detailed and applied to spatial and temporal aggregation of an agent-based model of international relations. The algorithm succeeds in providing meaningful high-level abstractions for the system analysis.

关键词： Data aggregation large-scale MAS algorithmic complexity spatial and temporal analysis news analysis

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Maximal Strip Recovery Problem with Gaps: Hardness and Approximation Algorithms

Maximal Strip Recovery Problem with Gaps: Hardness and Appro...

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20th International Symposium on Algorithms and Computations (ISAAC 2009)

作者： Bulteau, Laurent Fertin, Guillaume Rusu, Irena Ecole Normale Super 45 Rue Ulm F-75000 Paris France Univ Nantes CNRS Lab Informat Nantes Atlantique UMR 6241 F-44322 Nantes France

ISBN: (纸本)9783642106309

Given two comparative maps, that;is two sequences of markers each representing a genorne, the Maximal Strip Recovery problem (MSR) asks to extract a largest sequence of markers from each map such that the two extracted sequences are decomposable into non-overlapping strips (or synteny blocks). This aims at defining a robust set of synteny blocks between different species, which is a key to understand the evolution process since their last common ancestor. In this paper, we add a fundamental constraint to the initial problem, which expresses the biologically sustained need to bound the number of intermediate (non-selected) markers between two consecutive markers in a strip. We therefore introduce the problem delta-gap-MSR, where delta is a (usually small) non-negative integer that upper bounds the number of non-selected markers between two consecutive markers in a strip. Depending on the nature of the comparative maps (i.e., with or without duplicates), we show that delta-gap-MSR. is NP-complete for any delta >= 1, and even APX-hard for any delta >= 2. We also provide two approximation algorithms, with ratio 1.8 for delta = 1, and ratio 4 for delta >= 2.

关键词： algorithmic complexity approximation algorithms comparative maps genome comparison synteny blocks

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Some Theorems on Incremental Compression 1

引用

9th International Conference on Artificial General Intelligence (AGI) Held as Part of Joint Multi-Conference on Human-Level Intelligence (HLAI)

作者： Franz, Arthur Odessa Ukraine

ISBN: (数字)9783319416496

ISBN: (纸本)9783319416496;9783319416489

The ability to induce short descriptions of, i.e. compressing, a wide class of data is essential for any system exhibiting general intelligence. In all generality, it is proven that incremental compression extracting features of data strings and continuing to compress the residual data variance - leads to a time complexity superior to universal search if the strings are incrementally compressible. It is further shown that such a procedure breaks up the shortest description into a set of pairwise orthogonal features in terms of algorithmic information.

关键词： Incremental compression Data compression algorithmic complexity Universal induction Universal search Feature extraction

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A General Framework for Path Convexities 13th

A General Framework for Path Convexities

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13th International Conference on algorithmic Aspects in Information and Management (AAIM)

作者： Thompson, Joao Vinicius C. Nogueira, Loana T. Protti, Fabio Bravo, Raquel S. F. Dourado, Mitre C. Souza, Ueverton S. Ctr Fed Educ Tecnol Celso Suckow Fonseca Rio De Janeiro Brazil Univ Fed Fluminense Niteroi RJ Brazil Univ Fed Rio de Janeiro Rio De Janeiro Brazil

ISBN: (纸本)9783030271954;9783030271947

In this work we deal with the so-called path convexities, defined over special collections of paths. For example, the collection of the shortest paths in a graph is associated with the well-known geodesic convexity, while the collection of the induced paths is associated with the monophonic convexity;and there are many other examples. Besides reviewing the path convexities in the literature, we propose a general path convexity framework, of which most existing path convexities can be viewed as particular cases. Some benefits of the proposed framework are the systematization of the algorithmic study of related problems and the possibility of defining new convexities not yet investigated.

关键词： algorithmic complexity Graph convexity Path convexity

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CTG-Based Multiparametric Risk Stratification of Pregnant Women with Smoking Habit and Pregnant Women with IUGR 6

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6th European Conference of the International-Federation-for-Medical-and-Biological-Engineering (MBEC)

作者： Spyridou, Kyriaki Chouvarda, Ioanna Hadjileontiadis, Leontios Maglaveras, Nicos Aristotle Univ Thessaloniki Lab Med Informat Sch Med GR-54006 Thessaloniki Greece Aristotle Univ Thessaloniki Dept Elect & Comp Engn Polytech Sch Thessaloniki Greece

ISBN: (纸本)9783319111278

Different measures derived from linear and non linear fields are used in order to discriminate between normal fetuses and those exposed to cigarette smoking produced substances during pregnancy as well as fetuses with intra-uterine growth restriction (IUGR). There are computed parameters that indicate correlation or measures of complexity of the Fetal Heart Rate (FHR), in order to get closer to the core of information that the Cardiotocography (CTG) signal can convey and thus increase our understanding of FHR fluctuations. We analyzed signals recorded from 84 low risk pregnant women without any risk factor in a singleton pregnancy, 15 pregnant women with IUGR and 15 pregnant women that smoked during pregnancy. The analysis of FHR has shown that some parameters, such as Pearson Autocorrelation, Kurtosis and algorithmic complexity in cigarette-exposed fetuses as well as Hjorth Mobility in fetuses with IUGR could be used for early recognition of these potentially dangerous conditions and thus form biomarkers for risk stratification.

关键词： Cardiotocography pregnancy smoking IUGR algorithmic complexity non-linear analysis

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Assessing Parallel Algorithms 18

Assessing Parallel Algorithms

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18th International Conference on Soft Computing and Measurement (SCM)

作者： Baskakov, Yuriy Golubev, Ivan St Petersburg Electrotech Univ LETI Fac Comp Sci & Technol St Petersburg Russia

Various existing performance metrics within the parallel systems domain are analyzed. These include the different flavors of speedup, efficiency, and isoefficiency. Execution time still remains the most widely used me... 详细信息

ISBN: (纸本)9781467369619

关键词： parallel computing algorithmic complexity algorithmic cost models automatic algorithmic cost estimation

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On Hierarchical Compression and Power Laws in Nature 10th

On Hierarchical Compression and Power Laws in Nature

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10th International Conference on Artificial General Intelligence (AGI)

作者： Franz, Arthur Independent Researcher Odessa Ukraine

ISBN: (纸本)9783319637037;9783319637020

Since compressing data incrementally by a non-branching hierarchy has resulted in substantial efficiency gains for performing induction in previous work, we now explore branching hierarchical compression as a means for solving induction problems for generally intelligent systems. Even though assuming the compositionality of data generation and the locality of information may result in a loss of the universality of induction, it has still the potential to be general in the sense of reflecting the inherent structure of real world data imposed by the laws of physics. We derive a proof that branching compression hierarchies (BCHs) create power law functions of mutual algorithmic information between two strings as a function of their distance - a ubiquitous characteristic of natural data, which opens the possibility of efficient natural data compression by BCHs. Further, we show that such hierarchies guarantee the existence of short features in the data which in turn increases the efficiency of induction even more.

关键词： Hierarchical compression Incremental compression algorithmic complexity Universal induction Power laws Scale free structure

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Multicriteria Approaches for Predictive Model Generation: A Comparative Experimental Study

Multicriteria Approaches for Predictive Model Generation: A ...

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2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)

作者： Al-Jubouri, Bassma Gabrys, Bogdan Bournemouth Univ Fac Sci & Technol Smart Technol Res Ctr Poole BH12 5BB Dorset England

ISBN: (纸本)9781479944675

This study investigates the evaluation of machine learning models based on multiple criteria. The criteria included are: predictive model accuracy, model complexity, and algorithmic complexity (related to the learning/adaptation algorithm and prediction delivery) captured by monitoring the execution time. Furthermore, it compares the models generated from optimising the criteria using two approaches. The first approach is a scalarized multi objective optimisation, where the models are generated from optimising a single cost function that combines the criteria. On the other hand the second approach uses a Pareto-based multi objective optimisation to trade-off the three criteria and to generate a set of non-dominated models. This study shows that defining universal measures for the three criteria is not always feasible. Furthermore, it was shown that, the models generated from Pareto-based multi objective optimisation approach can be more accurate and more diverse than the models generated from scalarized multi objective optimisation approach.

关键词： Pareto optimisation computational complexity learning (artificial intelligence) prediction theory Pareto-based multiobjective optimisation adaptation algorithm algorithmic complexity learning algorithm machine learning models model complexity multicriteria approaches multiple criteria nondominated models prediction delivery predictive model accuracy predictive model generation scalarized multiobjective optimisation Accuracy Artificial neural networks complexity theory Mathematical model Optimization Prediction algorithms Predictive models Pareto optimisation algorithmic complexity Prediction theory Prediction algorithms complexity theory learning algorithms Prediction models Artificial neural networks complexity classes Mathematical Model machine model Multiple objective

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Path Planning for Robot Using Population-Based Incremental Learning 4

Path Planning for Robot Using Population-Based Incremental L...

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4th IEEE Annual International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

作者： Xu, Miao Lee, Jaesung Bahn, Sang-Kyu Kang, Bo-Yeong Kyungpook Natl Univ Sch Mech Engn Daegu South Korea Chung Ang Univ Sch Comp Sci & Engn Seoul 156756 South Korea

ISBN: (纸本)9781479936694

Recently, genetic algorithms (GAs) have attracted great interest owing to efficiency and flexibility against complex robot path planning problems. To accelerate the convergence speed, preceding researches adapted conventional GAs by using problem-specific techniques. However, such approaches increase computational burden and algorithmic complexity, resulting in subsequent additional problems. In this paper, we used Population-Based Incremental Learning (PBIL) algorithm for robot path planning as a probabilistic evolutionary approach. In addition to PBIL, we also proposed the probabilistic model of nodes and the edge bank to generate promising paths. The experimental results demonstrate that the proposed method gave markedly better performance than its conventional counterparts (GA,kGA,fGA) in terms of success rates and the quality of obtained paths.

关键词： Convergence Genetic algorithms Maintenance engineering Mathematical model Path planning Robots Safety Path planning Robot Maintenance engineering Genetic Algorithm (GA) Mathematical Model Converge Consumer safety safety learning (artificial intelligence) conventional gas algorithmic complexity Probabilistic Model

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Numerical Investigation of Graph Spectra and Information Interpretability of Eigenvalues 3

Numerical Investigation of Graph Spectra and Information Int...

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3rd International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO)

作者： Zenil, Hector Kiani, Narsis A. Tegner, Jesper Karolinska Inst Ctr Mol Med Dept Med Unit Computat Med Stockholm Sweden

ISBN: (纸本)9783319164809;9783319164793

We undertake an extensive numerical investigation of the graph spectra of thousands regular graphs, a set of random Erdos-Renyi graphs, the two most popular types of complex networks and an evolving genetic network by using novel conceptual and experimental tools. Our objective in so doing is to contribute to an understanding of the meaning of the Eigenvalues of a graph relative to its topological and information-theoretic properties. We introduce a technique for identifying the most informative Eigenvalues of evolving networks by comparing graph spectra behavior to their algorithmic complexity. We suggest that extending techniques can be used to further investigate the behavior of evolving biological networks. In the extended version of this paper we apply these techniques to seven tissue specific regulatory networks as static example and network of a naive pluripotent immune cell in the process of differentiating towards a Th17 cell as evolving example, finding the most and least informative Eigenvalues at every stage.

关键词： Network science graph spectra behavior algorithmic probability information content algorithmic complexity Eigenvalues meaning

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