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17th Workshop of Hybrid Intelligent Systems, HIS 2024, 17th Workshop on Intelligent Learning Environments, WILE 2024 and 6th Workshop on New Trends in Computational Intelligence and Applications, CIAPP 2024, held in conjunction with Mexican International Conference on Artificial Intelligence, MICAI 2024

作者： Ramos Herrera, Iván Alejandro Autonomous University of Aguascalientes Aguascalientes Mexico

ISBN: (纸本)9783031838781

The "Logarithmic Weighted Random Selector" (LWRS) introduces a novel algorithm designed for selecting randomly one item from a list, with the bias that the further to the beginning of the list each one is, the more likely it is to be selected. Unlike traditional selection and sampling methods that rely on numerical fitness scores or require hyperparameter tuning, LWRS employs a logarithmic weighting mechanism to naturally favor items based on their position. It arose from the problem of requiring a method that allows weighting a selection based on the order of preference on a list of elements, for phenomena for which numerical weighting values are unknown but only their order, which unlike algorithms such as Rank-based Selection, does not require configuration of hyperparameters. Different mechanisms were explored, such as a Linear Selection method and Exponential Selection. Discovering that utilizing a logarithmic scale, LWRS achieves a non-numerical preference bias, distinguishing itself from classic methods of weighted random sampling as Fitness-proportionate selection and Tournament Selection, which do require defined numerical weights, contributing to the field with a straightforward, parameter-free approach to weighted random selection. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： algorithm Design Computer Science Evolutionary Computing Random Sampling randomized algorithm Selection Method

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randomized probe selection algorithm for microarray design

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JOURNAL OF THEORETICAL BIOLOGY 2007年第3期248卷 512-521页

作者： Gasieniec, Leszek Li, Cindy Y. Sant, Paul Wong, Prudence W. H. Univ Liverpool Dept Comp Sci Liverpool L69 3BX Merseyside England

DNA microarray technology, originally developed to measure the level of gene expression, has become one of the most widely used tools in genomic study. The crux of microarray design lies in how to select a unique probe that distinguishes a given genomic sequence from other sequences. Due to its significance, probe selection attracts a lot of attention. Various probe selection algorithms have been developed in recent years. Good probe selection algorithms should produce a small number of candidate probes. Efficiency is also crucial because the data involved are usually huge. Most existing algorithms are usually not sufficiently selective and quite a large number of probes are returned. We propose a new direction to tackle the problem and give an efficient algorithm based on randomization to select a small set of probes and demonstrate that such a small set of probes is sufficient to distinguish each sequence from all the other sequences. Based on the algorithm, we have developed probe selection software RANDPS, which runs efficiently in practice. The software is available on our website (http://***/similar to cindy/RandPS/***). We test our algorithm via experiments on different genomes (Escherichia coli, Saccharamyces cercvisiae, etc.) and our algorithm is able to output unique probes for most of the genes efficiently. The other genes can be identified by a combination of at most two probes. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： randomized algorithm probe selection microarray design

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New parallel randomized algorithms for the traveling salesman problem

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COMPUTERS & OPERATIONS RESEARCH 1999年第4期26卷 371-394页

作者： Shi, LY Olafsson, S Sun, N Univ Wisconsin Dept Ind Engn Madison WI 53706 USA

We recently developed a new randomized optimization framework, the Nested Partitions (NP) method. This approach uses partitioning, global random sampling, and local search heuristics to create a Markov chain that has global optima as its absorbing states. This new method combines global and local search in a natural way and it is highly matched to emerging massively parallel processing capabilities. In this paper, we apply the NP method to the Travelling Salesman Problem. Preliminary numerical results show that the NP method generates high-quality solutions compared to well-known heuristic methods, and that it can be a very promising alternative for finding a solution to the TSP. (C) 1999 Elsevier Science Ltd. All rights reserved.

关键词： optimization randomized algorithm parallel algorithm traveling salesman problem

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HYPERMEDIA AND randomized algorithmS FOR MEDICAL EXPERT SYSTEMS

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 1990年第1期32卷 5-16页

作者： CHAVEZ, RM COOPER, GF Section on Medical Informatics Stanford University School of Medicine CA 94305.

KNET is an environment for constructing probabilistic, knowledge-intensive systems within the axiomatic framework of decision theory. The KNET architecture defines a complete separation between the hypermedia user interface on the one hand, and the representation and management of expert opinion on the other. KNET offers a choice of algorithms for probabilistic inference. We and our coworkers have used KNET to build consultation systems for lymph-node pathology, bone-marrow transplantation therapy, clinical epidemiology, and alarm management in the intensive-care unit. Most important, KNET contains a randomized approximation scheme (RAS) for the difficult and almost certainly intractable problem of Bayesian inference. Our algorithm can, in many circumstances, perform efficient approximate inference in large and richly interconnected models of medical diagnosis. In this article, we describe the architecture of KNET, construct a randomized algorithm for probabilistic inference, and analyze the algorithm's performance. Finally, we characterize our algorithms' empiric behavior and explore its potential for parallel speedups. From design to implementation, then, KNET demonstrates the crucial interaction between theoretical computer science and medical informatics.

关键词： Probabilistic expert system Computational complexity theory randomized algorithm Medical informatics

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randomized Pattern Formation algorithm for Asynchronous Oblivious Mobile Robots 28

Randomized Pattern Formation Algorithm for Asynchronous Obli...

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28th International Symposium on Distributed Computing

作者： Yamauchi, Yukiko Yamashita, Masafumi Kyushu Univ Fac Informat Sci & Elect Engn Fukuoka 812 Japan

ISBN: (纸本)9783662451748

We present a randomized pattern formation algorithm for asynchronous oblivious (i.e., memory-less) mobile robots that enables formation of any target pattern. As for deterministic pattern formation algorithms, the class of patterns formable from an initial configuration I is characterized by the symmetricity (i.e., the order of rotational symmetry) of I, and in particular, every pattern is formable from I if its symmetricity is 1. The randomized pattern formation algorithm psi(PF) we present in this paper consists of two phases: The first phase transforms a given initial configuration I into a configuration I' such that its symmetricity is 1, and the second phase invokes a deterministic pattern formation algorithm psi(CWM) by Fujinaga et al. (DISC 2012) for asynchronous oblivious mobile robots to finally form the target pattern. There are two hurdles to overcome to realize psi(PF). First, all robots must simultaneously stop and agree on the end of the first phase, to safely start the second phase, since the correctness of psi(CWM) is guaranteed only for an initial configuration in which all robots are stationary. Second, the sets of configurations in the two phases must be disjoint, so that even oblivious robots can recognize which phase they are working on. We provide a set of tricks to overcome these hurdles.

关键词： Mobile robot pattern formation randomized algorithm

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A method for obtaining randomized algorithms with small tail probabilities

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algorithmICA 1996年第4-5期16卷 543-547页

作者： Alt, H Guibas, L Mehlhorn, K Karp, R Wigderson, A STANFORD UNIV STANFORDCA 94305 DIGITAL EQUIPMENT CORP SYST RES CTRPALO ALTOCA 94301 UNIV SAARLAND MAX PLANCK INST INFORMATD-6600 SAARBRUCKENGERMANY UNIV SAARLAND FACHBEREICH INFORMATD-6600 SAARBRUCKENGERMANY INT COMP SCI INST BERKELEYCA 94704 UNIV CALIF BERKELEY BERKELEYCA 94720 HEBREW UNIV JERUSALEM DEPT COMP SCIIL-91905 JERUSALEMISRAEL PRINCETON UNIV DEPT COMP SCIPRINCETONNJ 07974

We study strategies for converting randomized algorithms of the Las Vegas type into randomized algorithms with small tail probabilities.

关键词： Las Vegas algorithms randomized algorithm tail probability

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A randomized Divide and Conquer algorithm for Higher-Order Abstract Voronoi Diagrams 25

A Randomized Divide and Conquer Algorithm for Higher-Order A...

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25th International Symposium on algorithms and Computation (ISAAC)

作者： Bohler, Cecilia Liu, Chih-Hung Papadopoulou, Evanthia Zavershynskyi, Maksym Univ Bonn Inst Comp Sci 1 D-53113 Bonn Germany USI Fac Informat Lugano Switzerland

ISBN: (纸本)9783319130750;9783319130743

Given a set of sites in the plane, their order-k Voronoi diagram partitions the plane into regions such that all points within one region have the same k nearest sites. The order-k abstract Voronoi diagram is defined in terms of bisecting curves satisfying some simple combinatorial properties, rather than the geometric notions of sites and distance, and it represents a wide class of order-k concrete Voronoi diagrams. In this paper we develop a randomized divide-and-conquer algorithm to compute the order-k abstract Voronoi diagram in expected O(kn(1+epsilon)) operations. For solving small sub-instances in the divide-and-conquer process, we also give two sub-algorithms with expected O(k(2)n log n) and O(n 2 2 a(n) log n) time, respectively. This directly implies an O(kn(1+epsilon))-time algorithm for several concrete order-k instances such as points in any convex distance, disjoint line segments and convex polygons of constant size in the L-p norm, and others.

关键词： Higher-Order Voronoi Diagram Abstract Voronoi Diagram randomized algorithm Divide and Conquer

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randomized algorithms for large-scale inverse problems with general Tikhonov regularizations

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INVERSE PROBLEMS 2015年第8期31卷 1-1页

作者： Xiang, Hua Zou, Jun Wuhan Univ Sch Math & Stat Wuhan 430072 Peoples R China Chinese Univ Hong Kong Dept Math Shatin Hong Kong Peoples R China

We shall investigate randomized algorithms for solving large-scale linear inverse problems with general Tikhonov regularizations. Our first approach transforms general form inverse problems into standard form, then we apply randomized algorithms to reduce large-scale systems of standard form to much smaller-scale systems and seek their regularized solutions in combination with some popular choice rules for regularization parameters. Our second approach involves a new random generalized SVD algorithm that can essentially reduce the sizes of the original large-scale ill-posed systems. The reduced systems can provide approximate regularized solutions with about the same accuracy as the ones by the classical generalized SVD, but they are much more stable and much less expensive as they need only to work on problems of much smaller sizes. Numerical results are presented to demonstrate the efficiency and accuracy of the algorithms.

关键词： generalized SVD randomized algorithm large-scale inverse problems

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Characterizations of semantic domains for randomized algorithms

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Japan Journal of Applied Mathematics 1989年第1期6卷 111-146页

作者： Yamada, Shinichi Department of Mathematics School of Science and Engineering Waseda University Shinjuku Tokyo 160 3-4-1 Ohkubo Japan Research and Advanced Technology Nihon Unisys Ltd. Tokyo 107 2-17-51 Akasaka Minato-ku Japan

randomized algorithms, or probabilistic algorithms, extend the notion of algorithm by introducing input of random data and random choices in the process of computation. A new mathematical theory of the semantic domains for randomized algorithms, or randomized domains, is developed, which intrinsically extends Scott's domain theory for deterministic computation. Main results include the characterization theorems and practical axiom systems for randomized domains, and the construction of the universal reflexive randomized domain R_∞. The theory readily provides denotational semantics for a class of high level probabilistic programming languages and is also directly applicable to probabilistic logics, inductive inference, and theory of stochastic programming. © 1989 JJAM Publishing Committee.

关键词： denotational semantics probabilistic programming languages randomized algorithm randomized domains

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Using randomized algorithms for digital mock-up in automotive industry

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Mexican International Conference on Artificial Intelligence (MICAI 2000)

作者： Bietzker, B Karch, O Noltemeier, H ISA Tools GMBH D-70567 Stuttgart Germany Univ Wurzburg Dept Comp Sci 1 D-97074 Wurzburg Germany

ISBN: (纸本)3540673547

An automobile consists of a large number of component parts that must be assembled. Even if all parts precisely fit together, it is not clear whether they can be assembled or not. The process of finding a suitable assembly sequence, which can be performed in reality, is called assembly planning. We present our probabilistic motion planner RAMONA developed in cooperation with Audi AG, Germany, which is used within a digital mock-up project for checking the feasibility of assembly sequences. The heart of RAMONA is a probabilistic complete motion planner, together with an efficient local path planner. We describe the basic concepts of our algorithm and investigate some details of the local planner.

关键词： assembly planning motion planning randomized algorithm adaptive search digital mock-up

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