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32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL 2024

作者： Van Damme, Marie-Dominique Méneroux, Yann Olteanu-Raimond, Ana-Maria Univ Gustave Eiffel IGN-ENSG LASTIG Saint-Mandé France

ISBN: (纸本)9798400711077

This paper focuses on GNSS trajectory aggregation, building upon the work of [4], a modular and iterative aggregation algorithm. The last allows to compute aggregated trajectories with high geometric accuracy for a set of trajectories having the same origin/destinations and following the same path. To analyze the performances of the algorithm, we use a metrological perspective, i.e. its ability to reconstruct the accurate aggregated trajectory, from a minimum number of input GNSS trajectory samples to determine an optimal parameterization of the algorithm. We validate our modular framework on two types of data: synthetic and experimental GNSS trajectories collected with multiple sensors under varying canopy conditions. © 2024 Copyright held by the owner/author(s).

关键词： consensus algorithm

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Reaching New Heights in Multi-Agent Collective Construction 27

Reaching New Heights in Multi-Agent Collective Construction

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Rameš, Martin Surynek, Pavel Faculty of Information Technology Czech Technical University Thákurova 9 Prague160 00 6 Czech Republic

ISBN: (纸本)9781643685489

We propose a new approach for multi-agent collective construction, based on the idea of reversible ramps. Our ReRamp algorithm utilizes reversible side-ramps to generate construction plans for ramped block structures higher and larger than was previously possible using state-of-the-art planning algorithms, given the same building area. We compare the ReRamp algorithm to similar state-of-the-art algorithms on a set of benchmark instances, where we demonstrate its superior computational speed. We also establish in our experiments that the ReRamp algorithm is capable of generating plans for a single-story house, an important milestone on the road to real-world multi-agent construction applications. © 2024 The Authors.

关键词： consensus algorithm

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On the Sample Complexity of Conditional Independence Testing with Von Mises Estimator with Application to Causal Discovery 41

On the Sample Complexity of Conditional Independence Testing...

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41st International Conference on Machine Learning, ICML 2024

作者： Jamshidi, Fateme Ganassali, Luca Kiyavash, Negar College of Management of Technology EPFL Lausanne Switzerland

Motivated by conditional independence testing, an essential step in constraint-based causal discovery algorithms, we study the nonparametric Von Mises estimator for the entropy of multivariate distributions built on a kernel density estimator. We establish an exponential concentration inequality for this estimator. We design a test for conditional independence (CI) based on our estimator, called VM-CI, which achieves optimal parametric rates under smoothness assumptions. Leveraging the exponential concentration, we prove a tight upper bound for the overall error of VM-CI. This, in turn, allows us to characterize the sample complexity of any constraint-based causal discovery algorithm that uses VM-CI for CI tests. To the best of our knowledge, this is the first sample complexity guarantee for causal discovery for non-linear models and non-Gaussian continuous variables. Furthermore, we empirically show that VM-CI outperforms other popular CI tests in terms of either time, sample complexity, or both. This enhancement significantly improves the performance in structure learning as well. Copyright 2024 by the author(s)

关键词： consensus algorithm

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A Near-Linear Time Approximation algorithm for Beyond-Worst-Case Graph Clustering 41

A Near-Linear Time Approximation Algorithm for Beyond-Worst-...

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41st International Conference on Machine Learning, ICML 2024

作者： Cohen-Addad, Vincent d'Orsi, Tommaso Mousavifar, Aida Google Research United States BIDSA Bocconi Italy

We consider the semi-random graph model of (Makarychev et al., 2012), where, given a random bipartite graph with α edges and an unknown bipartition (A, B) of the vertex set, an adversary can add arbitrary edges inside each community and remove arbitrary edges from the cut (A, B) (i.e. all adversarial changes are monotone with respect to the bipartition). For this model, a polynomial time algorithm is known to approximate the Balanced Cut problem up to value O(α) (Makarychev et al., 2012) as long as the cut (A, B) has size Ω(α). However, it consists of slow subroutines requiring optimal solutions for logarithmically many semidefinite programs. We study the fine-grained complexity of the problem and present the first near-linear time algorithm that achieves similar performances to that of (Makarychev et al., 2012). Our algorithm runs in time O(|V (G)|1+o(1) + |E(G)|1+o(1)) and finds a balanced cut of value O(α). Our approach appears easily extendible to related problem, such as Sparsest Cut, and also yields an near-linear time O(1)-approximation to Dagupta's objective function for hierarchical clustering (Dasgupta, 2016) for the semi-random hierarchical stochastic block model inputs of (Cohen-Addad et al., 2019). Copyright 2024 by the author(s)

关键词： consensus algorithm

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Follower Agnostic Learning in Stackelberg Games 63

Follower Agnostic Learning in Stackelberg Games

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Maheshwari, Chinmay Cheng, James Sastry, Shankar Ratliff, Lillian Mazumdar, Eric Uc Berkeley Eecs CA United States Uw Seattle Ece WA United States Caltech Cms and Economics CA United States

ISBN: (纸本)9798350316339

In this paper, we present an efficient algorithm to solve online Stackelberg games, featuring multiple followers, in a follower-agnostic manner. Unlike previous works, our approach works even when leader has no knowledge about the followers' utility functions, strategy space or learning algorithm. Our algorithm introduces a unique gradient estimator, leveraging specially designed strategies to probe followers. In a departure from traditional assumptions of optimal play, we model followers' responses using a convergent adaptation rule, allowing for realistic and dynamic interactions. The leader constructs the gradient estimator solely based on observations of followers' actions. We provide both non-asymptotic convergence rates to stationary points of the leader's objective and demonstrate asymptotic convergence to a local Stackelberg equilibrium. To validate the effectiveness of our algorithm, we use this algorithm to solve the problem of incentive design on a largescale transportation network, showcasing its robustness even when the leader lacks access to followers' demand information. © 2024 IEEE.

关键词： consensus algorithm

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Phonetic Redundancy Avoidance Technique 1

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4th International Conference on Smart Systems: Innovations in Computing, SSIC 2023

作者： Raykar, Nagesh Kumbharkar, Prashant Rangdale, Sonali Shri Jagdishprasad Jambharmal Timbrewala University Jhunjhunun India JSPMs Rajashri Shahu College of Engineering Pune411033 India

ISBN: (数字)9789819736904

ISBN: (纸本)9789819736898

Phonetic-based algorithm is beneficial to avoid the data redundancy. There are numerous Phonetic algorithm available such as Soundex, D-M Soundex, Metaphone, and Kolner Phonetic algorithm. The objective of this research is to develop modified phonetic algorithm to minimize data duplication. Our research focused on the existing three phonetic-based algorithm Daitch–Mokotoff Soundex, Kolner Phonetik Metaphone. The purpose of our research is apply modified version of phonetic algorithm to sample dataset to English names, European name, Jarman names, and verify the results. It is observed that phonetic algorithm used for many decades but there is no any universal Phonetic-based algorithm Existing Phonetic-based algorithm is used for the particular work. Like Daitch, Mokotoff Soundex algorithm is developed for the European-based Surname, it will show better result for ‘Slavic’- and ‘Yiddish’-based surnames. The Metaphone algorithm is developed for the English language. The Kolner phonetic-based algorithm developed for German language names or surnames. This is suitable for German names. In all scenario the Soundex phonetic algorithm in inconsistent so these Phonetic algorithm are to be enhanced. Our experimental results show 45.62% accuracy for Daitch–Mokotoff Soundex algorithm which is suitable for European Name, The Metaphone algorithm gives 93.25%. Useful for English language names and the Kolner Phonetik-based phonetic algorithm show 34.26% useful for the German Language, respectively. These phonetic-based algorithms are developed for the specific language;this is limitation of existing research so in current system proposed the universal algorithm which is more efficient than other phonetic algorithm. The developed phonetic-based algorithm gives the 98.00% accuracy for the all different kind of regional languages. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： consensus algorithm

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The Application of RRT Fast Search Tree algorithm in Route Planning and Obstacle Avoidance of Unmanned Vehicle

The Application of RRT Fast Search Tree Algorithm in Route P...

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作者： Cui, Jianhui Wu, Yuanyuan Zhai, Yongjian Liu, Zhaoqi Maritime College Tianjin University of Technology Tianjin300384 China Tianjin Navigation Instruments Research Institute Tianjin300131 China

The author proposes an improved bidirectional RRT-based local path planning algorithm for unmanned boats, with the goal of quickly planning optimal local obstacle avoidance paths for high-speed sailing unmanned boats. In order to address the problem of strong randomness in traditional bidirectional RRT algorithms and frequent twists and turns in the planned path, corner constraints are applied to each newly extended node. In response to the problem of traditional bidirectional RRT algorithm where two trees often cannot be smoothly connected, angle constraints and distance constraints are applied at the active connection points. A new dynamic step-size strategy was also proposed. The research results show that, in the case of no dynamic step-size strategy, the average convergence time of the improved two-way RRT algorithm after removing the maximum and minimum values is 24.375 ms, which is 14.706% more than that of the algorithm with dynamic step-size strategy. It is verified that the dynamic step-size strategy can accelerate the Search tree to jump out of the area around obstacles, thus reducing the convergence time of the algorithm. Research has shown that the improved algorithm has better path planning quality and shorter convergence time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： consensus algorithm

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DiverTEAM: An Effective Evolutionary algorithm for Diversified Top-k (Weight) Clique Search Problems 27

DiverTEAM: An Effective Evolutionary Algorithm for Diversifi...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Xue, Jinghui Zheng, Jiongzhi He, Kun Li, Chu-Min Liu, Yanli School of Computer Science and Technology Huazhong University of Science and Technology China MIS University of Picardie Jules Verne France WuHan University of Science and Technology China

ISBN: (纸本)9781643685489

In many real-world problems and applications, finding only a single element, even though the best, among all possible candidates, cannot fully meet the requirements. We may wish to have a collection where each individual is not only outstanding but also distinctive. Diversified Top-k (DTk) problems are a kind of combinatorial optimization problem for finding such a promising collection of multiple sub-structures, such as subgraphs like cliques and social communities. In this paper, we address two representative DTk problems, DTk Clique search (DTkC) and DTk Weight Clique search (DTkWC), and propose a novel and effective algorithm called Diversified Top-k Evolutionary algorithm (DiverTEAM) for the two problems. DiverTEAM consists of a local search algorithm, which focuses on generating high-quality and diverse individuals and sub-structures, and a genetic algorithm that makes individuals work as a team and converge to (near-)optima efficiently. Extensive experiments show the excellent and robust performance of DiverTEAM across various benchmarks of DTkC and DTkWC. © 2024 The Authors.

关键词： consensus algorithm

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Distributed Economic Dispatch for Energy Internet Based on Multiagent consensus Control

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第1期66卷 137-152页

作者： Chen, Wushun Li, Tao Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Shanghai Huawei Technol Co Ltd Shanghai 201206 Peoples R China East China Normal Univ Sch Math Sci Shanghai Key Lab Pure Math & Math Practice Shanghai 200241 Peoples R China

We consider the economic dispatch (ED) for an Energy Internet composed of energy routers (ERs), interconnected microgrids, and main grid. The microgrid consists of several bus nodes associated with distributed generators (DGs) and intelligent control units (ICUs). We propose a distributed ED algorithm for the grid-connected microgrid, where each ICU iterates the estimated electricity price of the distribution system and the estimation for the average power mismatch of the whole microgrid by leader-following and average-consensus algorithms, respectively. The ER iterates the incremental power exchanged with the distribution system. By constructing an auxiliary consensus system, we prove that if the communication topology of the Energy Internet contains a spanning tree with the ER as the root and there is a path from each ICU to the ER, then the estimated electricity price of the distribution system converges to its real value, the power supply and demand achieves balance and the ED achieves optimal asymptotically. Furthermore, we propose an autonomous distributed ED algorithm covering both grid-connected and isolated modes of the microgrid by feeding back the estimated average power mismatch for updating the incremental costs with penalty factor. It is proved that if the communication topology of the microgrid is connected and there exists an ICU bidirectionally neighboring the ER, then the microgrid can switch between the two modes reliably. The simulation results demonstrate the effectiveness of the proposed algorithms.

关键词： Microgrids Erbium Internet Estimation Topology Power supplies Switches consensus algorithm economic dispatch (ED) energy internet energy router (ER) multiagent system

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Weighted Average consensus-Based Optimization of Advection-Diffusion Systems

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2021年 7卷 45-61页

作者： Jafarizadeh, Saber Rakuten Mobile Inc Autonomous Networking Res & Innovat Dept Tokyo 1580094 Japan

As a fundamental algorithm for collaborative processing over multi-agent systems, distributed consensus algorithm has been studied for optimizing its convergence rate. Due to the close analogy between the diffusion problem and the consensus algorithm, the previous trend in the literature is to transform the diffusion system from the spatially continuous domain into the spatially discrete one. In this transformation, the optimality is not necessarily preserved. In this paper, the reverse of this approach has been adopted, and it has been shown that the optimality can be preserved. This paper studies optimization of the Continuous-Time consensus (CTC) problem on a weighted digraph with given average weight. Based on the detailed balance property, the CTC algorithm is converted into the weighted-average CTC algorithm. For the given distribution and average weight, a possible solution procedure has been provided. For finding the optimal weights corresponding to the weighted-average CTC algorithm with optimal convergence rate on a general graph. This solution procedure has been implemented based on the min-max theorem. For path topology, it is shown that the linearity of the drift term is the necessary and sufficient condition for the optimality of the consensus algorithm (and the corresponding diffusion system). Thus, the Pearson's class of discrete (continuous) distributions are optimal, where the closed-form formulas for the convergence rate, spectrum and other characteristics of the corresponding optimal consensus algorithm (diffusion system), i.e., the Hypergeometric types have been provided.

关键词： consensus algorithm Convergence Topology Mathematical model Optimization Lattices Eigenvalues and eigenfunctions Advection-diffusion continuous-time distributed consensus algorithms multi-agent system optimal convergence rate

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