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检索条件"任意字段=International Symposium on Programming and Systems"

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Resource Configuration in Naval Wargames with Incomplete Information and Multiple Constraints: A Coupled Confrontation Approach

Resource Configuration in Naval Wargames with Incomplete Inf...

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international symposium on Autonomous systems (ISAS)

作者： Dong Li Hongbin Ma College of Automation Beijing Institute of Technology Beijing China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

Resource configuration problems are very important in naval wargame and their agent design. Existing literature usually models the above problems from the perspective of unilateral optimization, and pays less attention to scenarios similar to this paper. This paper uses a typical naval wargame scenario as the background to study the resource configuration problem of ships under conditions of incomplete information and multiple constraints. We take the opponent’s optimization objectives and constraints into our own optimization and constraints, and innovatively propose a multi-objective integer programming optimization model with coupled confrontation. Then, the Pulp solution library was used to solve the possible ship one-on-one duel situation in the scenario, and two specific configuration plans for the problem were given using the idea of uncertain optimization. The results show that the model we proposed can solve the problem of ship resource configuration in naval wargame. This model can be widely applied to limited resource configuration problems in this type of imperfect information game.

关键词： Integer programming Uncertainty Autonomous systems Decision making Games Libraries Numerical models

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Adaptive dynamic programming approach for Stackelberg game-based fault-tolerant control

Adaptive dynamic programming approach for Stackelberg game-b...

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international symposium on Autonomous systems (ISAS)

作者： Yuhang Xu Bin Jiang Yizhen Meng College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Shanghai Aerospace Control Technology Institute Shanghai China Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai China

Game-based fault-tolerant control is one of the critical aspects in modern control system, and it becomes more challenging for large-scale interconnected systems. In this article, an adaptive dynamic programming (ADP) approach is established for solving the Stackelberg game-based fault-tolerant control problem of the interconnected systems. Two critic neural networks are constructed for approximating the solutions of Stackelberg equilibrium, in which a group of adaptive weight updating laws are proposed to ensure the uniform ultimate bounded property of the systems’ state as well as the weights of the critic neural networks. The outcomes of the simulations exhibit the efficacy of the designed approach.

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Human-Machine Interface Design for Industrial Robots

Human-Machine Interface Design for Industrial Robots

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international Artificial Intelligence and Data Processing symposium (IDAP)

作者： Yunus Furkan Öztürk Kerim Uslu Kadir Acar Dilek Bilgin Tükel Araştırma ve Geliştirme Altınay Robot Teknolojileri ARGE merkezi İstanbul Türkiye Yazılım Mühendisliği Departmanı Doğuş Üniversitesi İstanbul Türkiye

ISBN: (数字)9798331531492

ISBN: (纸本)9798331531508

With the extensive use of industrial robots, there is a growing need for user-friendly interfaces to ensure efficient and safe operation of these systems. Traditional Human-Machine Interfaces (HMI) can lead to user errors and production delays due to their complex structures and limited visual capabilities. This paper presents a new HMI design that simplifies the configuration of industrial robots, minimizes user errors, and enhances production efficiency. The developed bilingual interface features a user-friendly design specifically tailored for robot configuration, parameter settings, and programming processes, aiming to provide a seamless user experience.

关键词： Visualization Service robots Human-machine systems Production programming Industrial robots Data processing User experience Delays Artificial intelligence

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When Computing Power Network Meets Distributed Machine Learning: An Efficient Federated Split Learning Framework 31

When Computing Power Network Meets Distributed Machine Learn...

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31st IEEE/ACM international symposium on Quality of Service, IWQoS 2023

作者： Yuan, Xinjing Pu, Lingjun Jiao, Lei Wang, Xiaofei Yang, Meijuan Xu, Jingdong Institute of Systems and Networks College of Computer Science Nankai University China University of Oregon Department of Computer Science United States School of Computer Science and Technology Tianjin University China

ISBN: (纸本)9798350399738

In this paper, we advocate CPN-FedSL, a novel and flexible Federated Split Learning (FedSL) framework over Computing Power Network (CPN). We build a dedicated model to capture the basic settings and learning characteristics (e.g., training flow, latency and convergence). Based on this model, we introduce Resource Usage Effectiveness (RUE), a novel performance metric integrating training utility with system cost, and formulate a multivariate scheduling problem that maximizes RUE by comprehensively taking client admission, model partition, server selection, routing and bandwidth allocation into account (i.e., mixed-integer fractional programming). We design Refinery, an efficient approach that first linearizes the fractional objective and non-convex constraints, and then solves the transformed problem via a greedy based rounding algorithm in multiple iterations. Extensive evaluations corroborate that CPN-FedSL is superior to the standard and state-of-the-art learning frameworks (e.g., FedAvg and SplitFed), and besides Refinery is lightweight and significantly outperforms its variants and de facto heuristic methods under a variety of settings. © 2023 IEEE.

关键词： Integer programming

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Genetic programming Guidance for the Reentry Trajectory of the ReFEx Vehicle

Genetic Programming Guidance for the Reentry Trajectory of t...

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2024 IAF Space Transportation Solutions and Innovations symposium at the 75th international Astronautical Congress, IAC 2024

作者： Marchetti, Francesco Gutierrez, Jose Luis Redondo Seelbinder, David Institute of Space Systems Bremen Germany

ISBN: (纸本)9798331312244

In this work Genetic programming (GP) is used to obtain an alternative guidance law for online trajectory adaptation of the Reusability Flight Experiment (ReFEx) reentry vehicle. GP is an Evolutionary Algorithm (EA) capable of producing interpretable mathematical models that satisfies user defined objectives and constraints. It can be applied in a guidance setting, through direct interaction with the environment, learning to evolve a the guidance law to steer the vehicle towards the successful satisfaction of the mission. To the best of the authors' knowledge, the application of GP to a flight-ready vehicle represents a first in this domain and can help in increasing the TRL of this technique for Guidance and Control (G&C) applications. Furthermore, it produces interpretable models, in contrast to other Machine Learning (ML) approaches, and it can be applied to nonlinear models, in contrast with traditional methods. In this study, GP is applied offline to design an feedback guidance law to guide the ReFEx vehicle towards a desired final position in the presence of uncertainties in the physical models, navigation and control signals. The performance of the GP-based guidance law is compared against the current design, which defines the trajectory correction as an optimal control problem and reduces it to a nonlinear unconstrained optimization problem, which is then solved using a successive linearization strategy. The performance comparison between the two methods utilizes high fidelity 6-DoF Monte Carlo simulations. Capabilities, advantages and disadvantages of both methods are discussed and conclusions on the viability of the investigated GP approach are drawn. © 2024 international Astronautical Federation, IAF. All rights reserved.

关键词： Reentry

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Towards a Flexible Approach for Understanding and Comparing Traces 11th

Towards a Flexible Approach for Understanding and Compari...

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11th international symposium on From Data to Models and Back, DataMod 2023

作者： Bowles, Juliana K. F. SCCH Softwarepark 32a Hagenberg4232 Austria School of Computer Science University of St Andrews St AndrewsKY16 9SX United Kingdom

ISBN: (纸本)9783031872167

We assume given a set of behavioural models of computation (event structures) that can be extracted from specifications, processes, code and/or data depending on the application, and have labels containing additional information of interest (e.g., an integer variable representing a measure in the context of the computation). In this paper we present our vision towards a formal flexible approach to search for optimal traces of execution with respect to different parameters of interest (e.g., time, efficacy, cost and/or concurrency), enriched with a mechanism to understand the difference between (sub-optimal) traces and their formalisation as explanations. The underlying idea of the approach is to be generalisable and hence suited to tackle practical problems in a variety of domains from aerospace, automotive and automation industries, as well as systems and applications developed for healthcare. Our examples here come from a healthcare based context. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Integer programming

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Integer programming Approaches to an Issue of Scheduling for a Truck-Drone Last-Mile Delivery System with Parcel Pickup Service

Integer Programming Approaches to an Issue of Scheduling for...

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international symposium on Soft Computing and Intelligent systems (SCIS)

作者： Kotaro Yamada Yoshiyuki Karuno Hitoshi Iima Mechanodesign Program Graduate School of Science and Technology Kyoto Institute of Technology Kyoto Japan Faculty of Mechanical Engineering Kyoto Institute of Technology Kyoto Japan Faculty of Information and Human Sciences Kyoto Institute of Technology Kyoto Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

In this paper, we consider a scheduling issue for parcel delivery and pickup services by a truck-drone last-mile delivery system. We are given a single carrier truck and multiple identical drones to serve a finite set of customers. The single carrier truck plays the role of a mobile depot for the drones, and it visits several stops in a given order of them. The given order of stops constitutes a fixed truck route, and the carrier truck is allowed to launch (resp., to retrieve) a drone to (resp., from) a customer at a stop. For each sortie of a drone, the launching stop and the retrieving stop must be the same. The load capacity of a drone is limited to one, and for a sortie of a drone at a stop, there are three options: (i) only deliver a parcel to a customer, (ii) only pick up a parcel from a customer, and (iii) deliver a parcel to a customer, and then pick up a parcel from a customer. The scheduling problem asks to find an assignment of customers to drones with sortie options and a choice of a truck stop for each sortie in the assignment. The objective is to minimize the total duration of the carrier truck over all the stops, which is equivalent to minimizing the makespan. In this paper, we first propose an extended integer program for the case with both delivery and pickup services from an existing one for the case with delivery service only. We also conduct numerical experiments to demonstrate the solution quality of the proposed integer program by utilizing an integer programming solver, and report the results.

关键词： Integer programming Heuristic algorithms programming Batteries Drones Logistics

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Proceedings - 2022 21st international symposium on Parallel and Distributed Computing, ISPDC 2022

Proceedings - 2022 21st International Symposium on Parallel ...

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21st international symposium on Parallel and Distributed Computing, ISPDC 2022

ISBN: (纸本)9781665488020

The proceedings contain 19 papers. The topics discussed include: deep heuristic for broadcasting in arbitrary networks;online event selection for Mu3e using GPUs;estimating the impact of communication schemes for distributed graph processing;a scalable algorithm for homomorphic computing on multi-core clusters;APPFIS: an advanced parallel programming framework for iterative stencil based scientific applications in HPC environments;a hybrid clustering algorithm for high-performance edge computing devices;performance modeling of scalable resource allocations with the imperial PEPA compiler;and investigating TCP/MPTCP support for drop computing in user space network stacks.

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Test and Verification Environment and Methodology for Vernier Time-to-Digital Converter Pixel Array 24

Test and Verification Environment and Methodology for Vernie...

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24th international symposium on Design and Diagnostics of Electronic Circuits and systems (DDECS)

作者： Kadluhowski, Lukasz A. Kmon, Piotr AGH Univ Sci & Technol Fac Elect Engn Automat Comp Sci & Biomed Engn Dept Measurement & Elect Al A Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (纸本)9781665435956

The goal of building a system for precise time measurement in pixel radiation detectors motivates the development of flexible design and verification environment. It should be suitable for quick simulations when individual elements of the system are developed and should be scalable so that system-level verification is possible as well. The approach presented in this paper is to utilize the power of SystemVerilog language and apply basic Object-Oriented programming concepts to the test program. Since the design under test is a full-custom mixed-signal design, it must be simulated with AMS simulator and various features of analog design environment are used as well (Monte Carlo analysis, corner analysis, schematic capture GUI-related functions). The presented approach combines these two worlds and should be suitable for small academia projects, where design and verification is seldom done by separate teams.

关键词： System Verilog object-oriented programming time-to-digital converter pixel radiation detectors Vernier

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Multi-Issue Butterfly Architecture for Sparse Convex Quadratic programming 57

Multi-Issue Butterfly Architecture for Sparse Convex Quadrat...

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57th Annual IEEE/ACM international symposium on Microarchitecture, MICRO 2024

作者： Wang, Maolin McInerney, Ian Stellato, Bartolomeo Tu, Fengbin Boyd, Stephen So, Hayden Kwok-Hay Cheng, Kwang-Ting The Hong Kong University of Science and Technology Hong Kong Imperial College London United Kingdom Princeton University United States Stanford University United States University of Hong Kong Hong Kong

ISBN: (纸本)9798350350579

Convex quadratic optimization solvers are extensively utilized in various domains;however, achieving optimal performance in diverse situations remains a significant challenge due to the sparse nature of objective and constraint matrices. General-purpose architectures struggle with hardware utilization when performing critical sparse matrix operations, such as factorization and multiplication. To address this issue, we introduce a pipelined spatial architecture, Multi-Issue Butterfly (MIB), which supports all primitive scalar, vector, and matrix operations required by the Alternating Direction Method of Multipliers (ADMM) based solver algorithm. The proposed architecture features a butterfly computational network with innovative working modes for each node, controlled by runtime instructions. We developed a companion scheduling method for matrix operations based on their sparsity patterns. For factorization, an elimination tree guides the network instructions reordering to avoid data hazards caused by computation dependencies. For matrix-vector multiplication, data prefetching resolves structural hazards caused by read and write conflicts to register files. Instructions without hazards are issued simultaneously to increase pipeline throughput and function unit utilization. We evaluate the proposed architecture using FPGA prototypes, representing the first fully FPGA-based generic QP solver. Our assessment includes extensive performance and efficiency bench-marks across 100 QP problems from five application domains. Compared to the same algorithm variation running on CPU backends, our prototype achieves a geometric mean of 30.5× end-To-end speedup, 127.0 × greater energy efficiency, and 16.5× less runtime jitter. In comparison to GPU backends, the prototype attains a geometric mean of 4.3× faster end-To-end speedup, 21.7× higher energy efficiency, and 33.4× less runtime jitter. © 2024 IEEE.

关键词： Convex optimization

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