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greedy algorithm ALMOST DOMINATES IN SMOOTHED CONTEXTUAL BANDITS

SIAM JOURNAL ON COMPUTING 2023年第2期52卷 487-524页

作者： Raghavan, Manish Slivkins, Aleksandrs Vaughan, Jennifer Wortman Wu, Zhiwei Steven MIT Sloan Sch Management Cambridge MA 02142 USA Microsoft Res New York NY 10011 USA Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA

Online learning algorithms, widely used to power search and content optimization on the web, must balance exploration and exploitation, potentially sacrificing the experience of current users in order to gain information that will lead to better decisions in the future. While necessary in the worst case, explicit exploration has a number of disadvantages compared to the greedy algorithm that always "exploits" by choosing an action that currently looks optimal. We determine under what conditions inherent diversity in the data makes explicit exploration unnecessary. We build on a recent line of work on the smoothed analysis of the greedy algorithm in the linear contextual bandits model. We improve on prior results to show that the greedy algorithm almost matches the best possible Bayesian regret rate of any other algorithm on the same problem instance whenever the diversity conditions hold. The key technical finding is that data collected by the greedy algorithm suffices to simulate a run of any other algorithm. Further, we prove that under a particular smoothness assumption, the Bayesian regret of the greedy algorithm is at most (O) over tilde (T-1/3) in the worst case, where T is the time horizon.

关键词： multiarmed bandits linear bandits greedy algorithm smoothed analysis data diversity Bayesian regret

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greedy algorithm for Construction of Deterministic Decision Trees for Conventional Decision Tables from Closed Classes

Greedy Algorithm for Construction of Deterministic Decision ...

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International Joint Conference on Rough Sets (IJCRS)

作者： Ostonov, Azimkhon Moshkov, Mikhail King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn Div Thuwal 239556900 Saudi Arabia King Abdullah Univ Sci & Technol KAUST Computat Biosci Res Ctr Thuwal 239556900 Saudi Arabia

ISBN: (纸本)9783031656644;9783031656651

This paper examines specific classes of conventional decision tables (DTs) that are closed under operations of attribute (column) removal and decision modifications assigned to rows. For DTs belonging to any of these closed classes (CCs), we investigate a greedy algorithm that constructs a deterministic decision tree. We demonstrate that the number of steps performed by this algorithm is limited by twice the number of rows in the table. Furthermore, we compare the behavior of two functions. The first function describes the increase in the minimum complexity of a deterministic decision tree for a DT from the CC in the worst-case scenario, in relation to the complexity of the set of attributes associated with columns of the table. The second function characterizes the worst-case complexity growth of the deterministic decision tree constructed by the greedy algorithm for a DT from the CC, considering the growth of complexity of the set of attributes associated with columns of the table. We divide the entire collection of pairs consisting of a bounded complexity measure (BCM) and a CC into three subsets. For each subset, we establish lower and upper bounds for the second function based on the first function.

关键词： closed class of decision tables deterministic decision tree greedy algorithm

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Task Assignment for Multiple Multi-purpose Unmanned Aerial Vehicles Using greedy algorithm

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INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES 2024年第4期25卷 1380-1394页

作者： Jeon, Ha-Min Lim, Jae-Woo Ryoo, Changkyung Inha Univ Dept Aerosp Engn Incheon South Korea

Unmanned aerial vehicle fleets demand effective task assignment since the task scope of each vehicle depends on the task-specific equipment it carries. Here, we propose real-time task assignment for multiple multipurpose unmanned aerial vehicles using a greedy algorithm. The greedy algorithm does not require complex mathematical modeling and can respond to real-time situational changes due to its fast computation. The proposed algorithm uses the total flight time of all unmanned aerial vehicles as the objective function so that each vehicle completes all tasks within its available battery level. To increase the diversity of solutions, the algorithm is dually computed in the forward and backward directions from the starting and destination points, respectively. We apply the algorithm to water resource management and compare the results with those of mixed integer linear programming and the genetic algorithm. While the flight-time cost is similar across algorithms, computation is 3-8 times faster for the proposed algorithm than for the genetic algorithm. This advantage increases as the number of tasks and/or unmanned aerial vehicles increases. The proposed algorithm's consideration of remaining battery levels when selecting randomly unmanned aerial vehicles also results in a higher average remaining battery level than the other algorithms. These results suggest that the proposed algorithm shows promise and feasibility for application to real-time task assignment scenarios for multiple multipurpose unmanned aerial vehicles.

关键词： Task assignment greedy algorithm Mixed integer linear programming Genetic algorithm Multipurpose unmanned aerial vehicle Water resource management

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Back-and-Forth (BaF): a new greedy algorithm for geometric path planning of unmanned aerial vehicles

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COMPUTING 2024年第8期106卷 2811-2849页

作者： Aslan, Selcuk Erciyes Univ Dept Aeronaut Engn Kayseri Turkiye

The autonomous task success of an unmanned aerial vehiclel (UAV) or its military specialization called the unmanned combat aerial vehicle (UCAV) has a direct relationship with the planned path. However, planning a path for a UAV or UCAV system requires solving a challenging problem optimally by considering the different objectives about the enemy threats protecting the battlefield, fuel consumption or battery usage and kinematic constraints on the turning maneuvers. Because of the increasing demands to the UAV systems and game-changing roles played by them, developing new and versatile path planning algorithms become more critical and urgent. In this study, a greedy algorithm named as the Back-and-Forth (BaF) was designed and introduced for solving the path planning problem. The BaF algorithm gets its name from the main strategy where a heuristic approach is responsible to generate two predecessor paths, one of which is calculated from the start point to the target point, while the other is calculated in the reverse direction, and combines the generated paths for utilizing their advantageous line segments when obtaining more safe, short and maneuverable path candidates. The performance of the BaF was investigated over three battlefield scenarios and twelve test cases belonging to them. Moreover, the BaF was integrated into the workflow of a well-known meta-heuristic, artificial bee colony (ABC) algorithm, and detailed experiments were also carried out for evaluating the possible contribution of the BaF on the path planning capabilities of another technique. The results of the experiments showed that the BaF algorithm is able to plan at least promising or generally better paths with the exact consistency than other tested meta-heuristic techniques and runs nine or more times faster as validated through the comparison between the BaF and ABC algorithms. The results of the experiments further proved that the integration of the BaF boosts the performance of the ABC and

关键词： Back-and-Forth greedy algorithm Geometric path planning Unmanned aerial vehicles Artificial bee colony 68Txx

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Two-stage greedy algorithm based on crowd sensing for tour route recommendation

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APPLIED SOFT COMPUTING 2024年 153卷

作者： Zheng, Xiaoyao You, Hao Huang, He Sun, Liping Yu, Qingying Luo, Yonglong Anhui Normal Univ Sch Comp & Informat 189 South Jiuhua Rd Wuhu 241002 Anhui Peoples R China Soochow Univ Sch Comp Sci & Technol Suzhou 215000 Jiangsu Peoples R China

Currently, the demand for tourism is increasing, but traditional tour group routes have been unable to meet individual needs. This paper proposes a novel personalized recommendation method for tour routes based on crowd sensing. First, we utilize ArcMap to model a real road network. We then propose a novel scoring mechanism for points of interest, including an interest label matching score and crowd sensing score, and implement a user -personalized multi -constraint interest model. Based on whether a user has must -see scenic spots, we propose a variable neighborhood greedy tour recommendation algorithm for users with no must -see scenic spots and a single -multiple point of interest two -stage greedy tour route recommendation algorithm for users with must -see scenic spots. We collected real data regarding 200 attractions, 881 restaurants, 570 hotels and 28 mature travel routes in Beijing from Ctrip, Dianping and Tuniu. We perform case analysis on Beijing dataset and comparative experiments on Beijing and public datasets with the existing algorithms. The experimental results demonstrate that our algorithm has superior rationality and efficiency.

关键词： greedy algorithm Crowd sensing Tour route recommendation Multi-constraint

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Precise Retrieval of Sentinel-1 Data by Minimizing the Redundancy With greedy algorithm

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2024年 17卷 19478-19486页

作者： Yang, Kaiwen Zhang, Lei Wu, Jicang Qian, Jinsong Tongji Univ Coll Surveying & Geo Informat Shanghai 200092 Peoples R China Tongji Univ Coll Transportat Engn Shanghai 200092 Peoples R China

With a widespread adoption of synthetic aperture radar (SAR) observations in Earth sciences, the volume of annual data updates has soared to petabyte scales. Consequently, the accurate retrieval and efficient storage of SAR data have become pressing concerns. The existing data searching method exhibits significant redundancy, leading to wasteful consumption of bandwidth and storage resources. Aiming to address this issue, we present here an optimized retrieval method grounded in a greedy algorithm, which can substantially reduce redundant data by approximately 20-65% while ensuring comprehensive data coverage over the areas of interest. By significantly minimizing redundant data, the proposed method markedly enhances data acquisition efficiency and conserves storage space. Validation experiments with Sentinel-1 data, employing various keyhole markup language scope files as inputs, affirm the effectiveness and reliability of the method. The application of the proposed method is expected to pave the way for efficient data management and fully automatic InSAR processing.

关键词： Sentinel-1 Synthetic aperture radar Radar polarimetry Remote sensing Earth Satellites Termination of employment Orbits Optical sensors Optical imaging Data retrieval greedy algorithm sentinel-1 synthetic aperture radar (SAR)

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Fast identification of critical nodes in complex network based on improved greedy algorithm

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PHYSICA SCRIPTA 2024年第12期99卷 125282-125282页

作者： Sun, Yang Guo, Sijia Chen, Lei Li, Shengquan Shi, Dongdong Ding, Yipei Yangzhou Univ Coll Elect Energy & Power Engn Yangzhou 225127 Peoples R China

Over the past decades, many critical and complex systems, such as power grid, transportation network, and information network, have been effectively modeled using complex network. However, these networks are susceptible to cascading failure, triggered by minor failure, leading to partial or total collapse. Preventing cascading failure necessitates the protection of critical nodes within the network, making the identification of these nodes particularly crucial. In this paper, we introduce an Improved greedy algorithm (IGA), inspired by the traditional greedy algorithm and the relationship between the propagation mechanism of cascading failure and N-K failure. This algorithm gets rid of the shortcomings of traditional recognition algorithms for dealing with large-scale networks with long time and low accuracy, and evaluates the critical degree of nodes based on network connectivity and overload rate. The simulation is carried out in Barabsi-Albert (BA) network and IEEE 39-, 118-bus systems, and make comparisons with other different algorithms. The results show that IGA not only has low computational complexity, but also has high accuracy in identifying critical nodes in complex networks.

关键词： complex network cascading failure greedy algorithm N-K contingency

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An efficient mode shape-based RBF mesh deformation approach via forward-backward greedy algorithm in CFD/CSD coupled simulation

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JOURNAL OF FLUIDS AND STRUCTURES 2025年 133卷

作者： Gao, Xuehan He, Shun Gu, Yingsong Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China Natl Key Lab Strength & Struct Integr Xian 710072 Peoples R China

Mesh deformation is an important element of CFD/CSD coupled time marching simulation. A mode shape-based Radial Basis Functions interpolation (M-RBF) approach is proposed to improve the efficiency of mesh deformation in the time marching simulation. Inspired by the modal expansion theorem in vibration theory, a set of interpolation nodes is pre-selected according to the mode shapes, rather than the physical displacements at each individual time step. The data reduction scheme of the forward-backward greedy algorithm is developed to select an optimum set of interpolation nodes. The AGARD 445.6 wing, a benchmark model for transonic flutter prediction, and the Goland+ wing with a tip store, which presents complexities in both aerodynamic configuration and mode shapes, are employed to validate the accuracy, efficiency, and capability of the M-RBF approach. The results show that the optimum set of interpolation nodes can achieve the desired interpolation accuracy while having little effect on the mesh quality at all time steps. The traditional RBF mesh deformation (T-RBF) and the RBF mesh deformation method via forward greedy algorithm (G-RBF) method spent majority of CPU time on the linear system solution (approximately 99% and 77.6%, respectively) and the selection of interpolation nodes (about 87.7% and 91.9%, respectively) in the case of AGARD 445.6 and Goland+ wing. However, by eliminating the need for repeated node selections, our M-RBF approach can improve the efficiency of mesh deformation by 2 to 3 orders of magnitude compared to the T-RBF method and 1 to 2 orders of magnitude compared to the G-RBF approach. The comparison of selected interpolation nodes by the M-RBF approach to the structural grid and CFD mesh indicates that the importance of nodes on the deforming boundary may be related to their distances from the structural grid.

关键词： Mesh deformation greedy algorithm Radial basis function CFD/CSD coupled time marching simulation

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Space Debris Sky Survey Observation Strategy Based on HEALPix and greedy algorithm

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AEROSPACE 2025年第3期12卷 168-168页

作者： Liu, Shuqi Hu, Shaoming Du, Junju Cao, Hai Zhang, Bo Jiang, Yuchen Feng, Shuai Shandong Univ Inst Space Sci Sch Space Sci & Technol Shandong Key Lab Opt Astron & Solar Terr Environm Weihai 264209 Peoples R China

To improve the observation efficiency of space debris surveys, a basic sky survey observation strategy was developed, with the aim of observing more space debris based on the Wide Field Optical Telescope Array run by Shandong University. The characteristics of the telescope and dynamic changes in the movement and position of space debris are considered in this strategy. An objective function was designed based on these factors. Using the pixelated sphere method to finely divide the celestial area, applying the summation filtering method, and using a greedy algorithm, the benefit of the objective function can be maximized, thus generating the optimal sky survey observation strategy. Through simulation and observation experiments, we demonstrate that the greedy algorithm observation strategy significantly improves the number of space debris instances and the number of arc segments with respect to the conventional observation strategy. This not only improves the automation level of space debris observation tasks, but also significantly enhances the execution efficiency of telescopes for debris observation. It is very helpful for cataloging space debris and generating collision warnings.

关键词： observation strategy pixelized sphere objective function greedy algorithm

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Martingale type, the Gamlen-Gaudet construction and a greedy algorithm

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JOURNAL OF FUNCTIONAL ANALYSIS 2024年第9期286卷

作者： Kazaniecki, Krystian Mueller, Paul F. X. Johannes Kepler Univ Linz Inst Anal Altenberger Str 69 A-4040 Linz Austria Univ Warsaw Inst Math Ul Banacha 2 PL-02097 Warsaw Poland

In the present paper we identify those filtered probability spaces (Omega, F, (F-n), P) that determine already the martingale type of a Banach space X. We isolate intrinsic conditions on the filtration (F-n) of purely atomic sigma-algebras which determine that the upper l(p) estimates parallel to f parallel to(p)(Lp(Omega, X)) <= C-p (parallel to E(f vertical bar F-0)parallel to(p)(Lp(Omega, X)) + Sigma(infinity)(n=1) parallel to E(f vertical bar F-n)- E(f vertical bar Fn-1)parallel to(p)(Lp(Omega,X))), f is an element of L-p(Omega, X) imply that the Banach space X is of martingale type p. Our paper complements G. Pisier's investigation [12] and continues the work by S. Geiss and second named author in [3]. (c) 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Martingale type Gamlen-Gaudet constructions Carleson constant greedy algorithm

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