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检索条件"主题词=Searching algorithm"

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Distributed Search for Pure Nash Equilibria in Graphical Games 16

Distributed Search for Pure Nash Equilibria in Graphical Gam...

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International Conference on Autonomous Agents and Multiagent Systems

作者： Omer Litov Amnon Meisels Department of Computer Science Ben-Gurion University of the Negev

ISBN: (纸本)9781510855083

Graphical games introduce a compact representation, where agents' outcomes depend only on their neighbors. A distributed search algorithm for pure Nash equilibria of graphical games is presented. The algorithm uses the analogy of graphical games with asymmetric distributed constraints optimization problems (ADCOPs). The proposed algorithm includes three components - an admissible pruning heuristic; a back-checking mechanism; and a pseudo tree representation of the game. An experimental evaluation of the components of the proposed search algorithm is presented for randomly generated networks of multiple agents. The major speedup over a naive search algorithm is shown to arise from the use of a pseudo tree representation. A simple assessment method of the privacy loss due to back-checking is presented and is shown to result in a tradeoff between the performance of the complete algorithm and its privacy loss.

关键词： algorithms Distributed problem solving DCOP Nash equilibrium Privacy Nash equilibrium distributed problem solving Privacy algorithms Game theory searching algorithm distributed search

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JOINT SOURCE-CHANNEL RATE CONTROL FOR MULTIVIEW VIDEO STREAMING OVER ERASURE CHANNELS

JOINT SOURCE-CHANNEL RATE CONTROL FOR MULTIVIEW VIDEO STREAM...

引用

IEEE International Conference on Image Processing

作者： Weiliang Xu Junni Zou Hongkai Xiong School of Communication Engineering Shanghai University Department of Electronic Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781467399623

To enable robust multiview video streaming over current wireless broadcast infrastructures, this paper proposes a joint source and channel coding optimization framework for video streaming based upon multiview video coding technique. It utilizes random linear coding (RLC) with ladder-shaped global coding coefficient matrix (GCM) for unequal erasure protection. An accurate expression of the decoding probability for RLC with ladder-shaped GCM is derived. A fast two-layer local search algorithm is developed to solve the source and channel coding rate allocation problem, where the source and channel rate of each layer can be adjusted independently for the overall video quality. Simulation results demonstrate significant video quality improvement to existing rate allocation schemes.

关键词： Interactive multiview video streaming Scheduling Fairness Asymmetric bargaining game Videotapes ITGA9 gene searching algorithm radio link control Combined source-channel coding Video streaming channel rate Joints General circulation models Standing Orders

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Enhanced observation scheduling method for space situational awareness

Enhanced observation scheduling method for space situational...

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SICE Annual Conference

作者： Kazuki Hirashima Shusuke Watanabe Megumi Sawada Atsuo Ozaki Information Technology R&D Center Mitsubishi Electric Corporation.

ISBN: (纸本)9781509009374

The observation scheduling method for Space Situational Awareness (SSA) that prioritizes only Observation Effectiveness (OE) has a low completion rate for user requests. In this study, we present the results from our analysis of the method of scheduling Resident Space Objects (RSO: satellites and their debris orbiting the earth) in Low Earth Orbit (LEO) that prioritizes OE and Request Completion Rate (RCR). First, we analyzed the limitations of the existing method, and then, we designed a new method that increases the RCR of the requests having a high average value of OE. The proposed method results in an improvement of 16.1% in the completion rate of high-priority requests and a reduction of only 0.063 in the average OE when compared with the corresponding results from the method that prioritizes only OE. Further, we applied a local search algorithm to improve the schedule that we created.

关键词： Space Situational Awareness Space Debris Observation Scheduling Local Search algorithm situational awareness Space debris Awareness Radio Control Relay searching algorithm Completion

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Efficient algorithm for Baseband Unit Pool Planning in Cloud Radio Access Networks

Efficient Algorithm for Baseband Unit Pool Planning in Cloud...

引用

IEEE Vehicular Technology Conference

作者： Sheng Xu Shaowei Wang School of Electronic Science and Engineering Nanjing University

ISBN: (纸本)9781509016990

Cloud Radio Access Network (C-RAN) is deemed as a promising architecture to enhance the spectrum and energy efficiency of the cellular systems. The key feature of the C-RAN is that most of signal processing functions are conducted in a centralized baseband unit (BBU) pool. As a result, the remote radio heads (RRHs) that are relatively simple can be distributed in the large network in a cost-efficient manner. In this paper, we investigate the BBU pool placement problem in the C-RAN, where we try to minimize the deployment cost of the BBUs while considering their processing capacities, the traffic demands of RRHs and the signal synchronization between RRHs and BBUs. Our general problem formulation leads to an NP-hard integer programming optimization task. We propose an efficient local search algorithm to address it. Numerical results show that the proposed algorithm converges quickly and always yields a performance-guaranteed solution to the BBU pool planning.

关键词： BBU pool planning C-RAN Local search efficient algorithm Wireless networks POOLS Problem Formulation Clouds searching algorithm signal processing Energy efficiency

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Beyond Fixed Neighborhood Search in the Likelihood Ascent algorithm for MIMO Systems

Beyond Fixed Neighborhood Search in the Likelihood Ascent Al...

引用

Ad-Hoc and Sensor Networks Symposium

作者： Abhay Kumar Sah A. K. Chaturvedi Department of Electrical Engineering Indian Institute of Technology Kanpur

ISBN: (纸本)9781479966653

Neighborhood search algorithms have been proposed for detection in large/massive multiple-input multiple-output (MIMO) systems. They iteratively search for the best vector in a fixed neighborhood. However, the ML solution may not lie in the searched space or the search may take a large number of intermediate vectors to converge. Instead of searching in a fixed neighborhood, a better way will be to look for an update which is not restricted to be in a fixed neighborhood. Motivated by this, we formulate an optimization problem to maximize the reduction in ML cost and use it to derive an expression for updating the solution. We use a metric based on the channel matrix and the error vector to determine the likelihood of a symbol being in error. Using this likelihood and the update, we propose a likelihood ascent search (LAS) algorithm to find an update which is not restricted to be in a fixed neighborhood and seeks to provide maximum reduction in ML cost. This process continues till there is a reduction in the ML cost. Compared to existing LAS based algorithms, it is found to provide better error performance, that too at a lower complexity.

关键词： multiple input multiple output systems Error vector Neighborhood Computer Programming Languages error performance channel matrix Likelihood Fixed ascent searching algorithm Searches

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Finding Perfect Matchings in Bipartite Hypergraphs 16

Finding Perfect Matchings in Bipartite Hypergraphs

引用

Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete algorithms

作者： Chidambaram Annamalai Department of Computer Science

ISBN: (纸本)9781510819672

Haxell's condition [16] is a natural hypergraph analog of Hall's condition, which is a well-known necessary and sufficient condition for a bipartite graph to admit a perfect matching. That is, when Haxell's condition holds it forces the existence of a perfect matching in the bipartite hypergraph. Unlike in graphs, however, there is no known polynomial time algorithm to find the hypergraph perfect matching that is guaranteed to exist when Haxell's condition is satisfied. We prove the existence of an efficient algorithm to find perfect matchings in bipartite hypergraphs whenever a stronger version of Haxell's condition holds. Our algorithm can be seen as a generalization of the classical Hungarian algorithm for finding perfect matchings in bipartite graphs. The techniques we use to achieve this result could be of use more generally in other combinatorial problems on hypergraphs where disjointness structure is crucial, e.g. Set Packing.

关键词： Bipartite hypergraphs Matchings Local search algorithms Perfect TWO-COMPONENT hypergraph searching algorithm Bipartite graph FINDINGS efficient algorithm algorithms

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A Multi-objective Optimization algorithm for Bus Type Assignments in Random Topology Power Grid Model

A Multi-objective Optimization Algorithm for Bus Type Assign...

引用

Hawaii International Conference on System Sciences

作者： Seyyed H. Elyas Zhifang Wang Virginia Commonwealth Univ. Richmond VA USA

ISBN: (纸本)9781509019816

Our previous work proposed a random topology power grid model, called RT-nested-smallworld, formulated based on a comprehensive study of the real-world grid topologies and electrical properties. The model can be used to produce a sufficiently large number of power grid test cases with scalable network size and featuring the same kind of small-world topology and electrical characteristics found in realistic grids. However, the proposed RT-power grid model has a shortcoming that is its random assignment of bus types (i.e. Generation, Load, or Connection), which is inconsistent with that of a realistic grid. Because our recent study found that the bus type assignment in a realistic power grid is not random but a correlated one. With the help of Bus Type Entropy, a novel measure which provides a quantitative means to better represent the correlation of bus type assignments in a grid topology, we propose a multi-objective optimization algorithm for the bus type assignments in the random topology power grid modeling. The proposed search algorithm is able to locate the best set of bus type assignments for a given random "electrical" topology generated by RT-nested-smallworld, so that each bus type assignment in the target set will have a Bus Type Entropy value close to that of a realistic grid with comparable network size. In order to demonstrate the performance of the proposed multi-objective algorithm, we experiment our algorithm on three sets of realistic power systems, namely, the IEEE-300 bus system, the NYISO system and the MPC system. The obtained results confirm the validity of our proposed method.

关键词： Power grids Motor buses Optimization algorithms searching algorithm topology target setting Room temperature grids Grid Randomisation

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Non-parametric contextual stochastic search

Non-parametric contextual stochastic search

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Abbas Abdolmaleki Nuno Lau Luis Paulo Reis Gerhard Neumann DETI/IEETA University of Aveiro Portugal LIACC University of Porto Portugal CLAS IAS TU Darmstadt Germany

ISBN: (纸本)9781509037636

Stochastic search algorithms are black-box optimizer of an objective function. They have recently gained a lot of attention in operations research, machine learning and policy search of robot motor skills due to their ease of use and their generality. Yet, many stochastic search algorithms require relearning if the task or objective function changes slightly to adapt the solution to the new situation or the new context. In this paper, we consider the contextual stochastic search setup. Here, we want to find multiple good parameter vectors for multiple related tasks, where each task is described by a continuous context vector. Hence, the objective function might change slightly for each parameter vector evaluation of a task or context. Contextual algorithms have been investigated in the field of policy search, however, the search distribution typically uses a parametric model that is linear in the some hand-defined context features. Finding good context features is a challenging task, and hence, non-parametric methods are often preferred over their parametric counter-parts. In this paper, we propose a non-parametric contextual stochastic search algorithm that can learn a non-parametric search distribution for multiple tasks simultaneously. In difference to existing methods, our method can also learn a context dependent covariance matrix that guides the exploration of the search process. We illustrate its performance on several non-linear contextual tasks.

关键词： searching algorithm Objective function Search process Stochastic variance covariance matrix Policies Religious Missions

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An Adaptive Harmony Search algorithm based on Positive Feedback for Network Reconfiguration

An Adaptive Harmony Search Algorithm based on Positive Feedb...

引用

IEEE Power and Energy Society General Meeting

作者： Zhi Li Yuqi Han Yu Zhang Yingkai Bao Chuangxin Guo Jianmin Zhang College of Electrical Engineering Zhejiang University College of Electrical Engineering and Automation Hangzhou Dianzi University

ISBN: (纸本)9781509041695

Distribution network reconfiguration is a complex and discrete nonlinear combinatory optimization problem. In this paper, an adaptive harmony search algorithm based on positive feedback (PFAHSA) is proposed to solve the problem for reducing power loss in distribution systems. The PFAHSA incorporates a local optimal method based on positive feedback mechanism into traditional harmony improvising criteria for better utilization of harmony memory (HM) and higher convergence speed. The algorithm parameters are updated adaptively by modified entropy, which measures the diversity of HM, to avoid prematurity and improve search success rate. The proposed method is testified on the IEEE 33- and 69-bus systems and is compared with other conventional approaches. Simulation results show that the proposed method features faster optimization speed and better global convergence performance.

关键词： Distribution network reconfiguration Harmony search algorithm Positive feedback mechanism Entropy Adaptive parameter setting Network reconfiguration searching algorithm entropy Positive feedback HEALTH MONITORING feedback mechanism dispensing system

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A distributed deterministic spiral search algorithm for swarms

A distributed deterministic spiral search algorithm for swar...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： G. Matthew Fricke Joshua P. Hecker Antonio D. Griego Linh T. Tran Melanie E. Moses Computer Science Department University of New Mexico Albuquerque USA

ISBN: (纸本)9781509037636

As robot swarms become more viable, efficient solutions to fundamental tasks such as swarm search and collection are required. We propose the distributed deterministic spiral algorithm (DDSA) which generalises a spiral search pattern to robot swarms. While being an effective search strategy in its own right, the DDSA is also a useful point of comparison for other swarm search strategies. Such a benchmark for robot swarm search is currently needed but missing. As a case study, we compare the DDSA to a biologically-inspired central-place foraging algorithm that uses stochastic search, memory, and communication to efficiently collect resources in a variety of different resource distributions.

关键词： swarms search strategies searching algorithm search memory Spiral dike swarms Robot deterministic

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