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16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023

作者： Yao, Guangyu Zhang, Nan Duan, Zhenhua Tian, Cong Institute of Computing Theory and Technology and ISN Laboratory Xidian University Xi’an710071 China

ISBN: (纸本)9783031496134

Path planning in complex environments has always been a focus of research for scholars both domestically and internationally. This study addresses the challenge of path planning that combines obstacle avoidance and optimal path searching in scenarios lacking prior knowledge. The proposed approach introduces a parameter dynamic adaptation strategy for path planning. Experimental investigations are conducted using grid-based maps, and the results demonstrate that the method presented in this paper surpasses Q-learning and Sarsa algorithms in terms of comprehensive exploration, enhanced stability, and quicker convergence speed. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Reinforcement learning

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An Approach to Agent Path Planning Under Temporal Logic Constraints 29th

An Approach to Agent Path Planning Under Temporal Logic Cons...

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29th International computing and Combinatorics Conference, COCOON 2023

作者： Yu, Chaofeng Zhang, Nan Duan, Zhenhua Tian, Cong Institute of Computing Theory and Technology and ISN Laboratory Xidian University Xi’an710071 China

ISBN: (纸本)9783031491924

The capability of path planning is a necessity for an agent to accomplish tasks autonomously. Traditional path planning methods fail to complete tasks that are constrained by temporal properties, such as conditional reachability, safety, and liveness. Our work presents an integrated approach that combines reinforcement learning (RL) with multi-objective optimization to address path planning problems with the consideration of temporal logic constraints. The main contributions of this paper are as follows. (1) We propose an algorithm LCAP 2 to design extra rewards and accelerate training by tackling a multi-objective optimization problem. The experimental results show that the method effectively accelerates the convergence of the path lengths traversed during the agent’s training. (2) We provide a convergence theorem based on the fixed-point theory and contraction mapping theorem. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Temporal logic

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Three Algorithms for Converting Control Flow Statements from Python to XD-M 16th

Three Algorithms for Converting Control Flow Statements fro...

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16th International Conference on Algorithmic Aspects in Information and Management, AAIM 2022

作者： Wang, Jiarui Zhang, Nan Duan, Zhenhua Institute of Computing Theory and Technology and ISN Laboratory Xidian University Xi’an710071 China

ISBN: (纸本)9783031160806

This paper presents an approach to show how to implement three complex statements: continue, break, return of Python to XD-M language. To this end, three algorithms for implementing three complex statements are given in detail. Further, three complex statements are implemented in XD-M. Finally, a program example is presented to illustrate how to use the proposed approach to build an XD-M program equivalent to the original Python program. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Python

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ParMod: A Parallel and Modular Framework for Learning Non-Markovian Tasks

arXiv

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arXiv 2024年

作者： Miao, Ruixuan Lu, Xu Tian, Cong Yu, Bin Duan, Zhenhua Institute of Computing Theory and Technology State Key Laboratory of ISN Xidian University China

The commonly used Reinforcement Learning (RL) model, MDPs (Markov Decision Processes), has a basic premise that rewards depend on the current state and action only. However, many real-world tasks are non-Markovian, which has long-term memory and dependency. The reward sparseness problem is further amplified in non-Markovian scenarios. Hence learning a non-Markovian task (NMT) is inherently more difficult than learning a Markovian one. In this paper, we propose a novel Parallel and Modular RL framework, ParMod, specifically for learning NMTs specified by temporal logic. With the aid of formal techniques, the NMT is modulaized into a series of sub-tasks based on the automaton structure (equivalent to its temporal logic counterpart). On this basis, sub-tasks will be trained by a group of agents in a parallel fashion, with one agent handling one sub-task. Besides parallel training, the core of ParMod lies in: a flexible classification method for modularizing the NMT, and an effective reward shaping method for improving the sample efficiency. A comprehensive evaluation is conducted on several challenging benchmark problems with respect to various metrics. The experimental results show that ParMod achieves superior performance over other relevant studies. Our work thus provides a good synergy among RL, NMT and temporal logic. © 2024, CC BY.

关键词： Contrastive Learning

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Design and Implementation of List and Dictionary in XD-M Language 15th

Design and Implementation of List and Dictionary in XD-M...

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15th International Conference on Algorithmic Aspects in Information and Management, AAIM 2021

作者： Wang, Yajie Zhang, Nan Duan, Zhenhua Institute of Computing Theory and Technology and ISN Laboratory Xidian University Xi’an710071 China

ISBN: (纸本)9783030931759

This paper presents the design and implementation of two data types, List and Dictionary, in the programming language XD-M. XD-M is an interpreted language with dynamic data types and its syntax is similar to Python. It is developed from the Modeling Simulation and Verification Language called MSVL. In the main part of the paper, we will discuss data structures, syntax and algorithms of List and Dictionary in XD-M, as well as their abstract syntax trees. Finally, an example is given to illustrate how to use List and Dictionary in XD-M programming. © 2021, Springer Nature Switzerland AG.

关键词： Data structures

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AutoSketch: Automatic Sketch-Oriented Compiler for Query-driven Network Telemetry 21

AutoSketch: Automatic Sketch-Oriented Compiler for Query-dri...

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21st USENIX Symposium on Networked Systems Design and Implementation, NSDI 2024

作者： Sun, Haifeng Huang, Qun Sun, Jinbo Wang, Wei Li, Jiaheng Li, Fuliang Bao, Yungang Yao, Xin Zhang, Gong National Key Laboratory for Multimedia Information Processing School of Computer Science Peking University China Institute of Computing Technology CAS China Northeastern University China Huawei Theory Department

ISBN: (纸本)9781939133397

Recent network telemetry witnesses tremendous progress in two directions: query-driven telemetry that targets expressiveness as the primary goal, and sketch-based algorithms that address resource-accuracy trade-offs. In this paper, we propose AutoSketch that aims to integrate the advantages of both classes. In a nutshell, AutoSketch automatically compiles high-level operators into sketch instances that can be readily deployed with low resource usage and incur limited accuracy drop. However, there remains a gap between the expressiveness of high-level operators and the underlying realization of sketch algorithms. AutoSketch bridges this gap in three aspects. First, AutoSketch extends its interface derived from existing query-driven telemetry such that users can specify the desired telemetry accuracy. The specified accuracy intent will be utilized to guide the compiling procedure. Second, AutoSketch leverages various techniques, such as syntax analysis and performance estimation, to construct efficient sketch instances. Finally, AutoSketch automatically searches for the most suitable parameter configurations that fulfill the accuracy intent with minimum resource usage. Our experiments demonstrate that AutoSketch can achieve high expressiveness, high accuracy, and low resource usage compared to state-of-the-art telemetry solutions. © 2024 Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, NSDI 2024. All rights reserved.

关键词： Economic and social effects

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Quantum frontiers in high energy physics

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Science China(Physics,Mechanics & Astronomy) 2025年第6期Mechanics & Astronomy) .卷 53-75页

作者： Yaquan Fang Christina Gao Ying-Ying Li Jing Shu Yusheng Wu Hongxi Xing Bin Xu Lailin Xu Chen Zhou Institute of High Energy Physics Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Physics Southern University of Science and Technology Interdisciplinary Center for Theoretical Study University of Science and Technology of China Peng Huanwu Center for Fundamental Theory State Key Laboratory of Nuclear Physics and Technology School of Physics Peking University Center for High Energy Physics Peking University Beijing Laser Acceleration Innovation Center State Key Laboratory of Particle Detection and Electronics Department of Modern Physics University of Science and Technology of China Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum MatterSouth China Normal University Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear ScienceSouthern Nuclear Science Computing Center South China Normal University Southern Center for Nuclear-Science Theory Institute of Modern Physics Chinese Academy of Sciences

Numerous challenges persist in high energy physics(HEP), the addressing of which requires advancements in detection technology, computational methods, data analysis frameworks, and phenomenological designs. We provide a concise yet comprehensive overview of recent progress across these areas, in line with advances in quantum technology. We will discuss the potential of quantum devices in detecting subtle effects indicative of new physics BSM, the transformative role of quantum algorithms and large-scale quantum computers in studying real-time non-perturbative dynamics in the early universe and at colliders, as well as in analyzing complex HEP data. Additionally, we emphasize the importance of integrating quantum properties into HEP experiments to test quantum mechanics at unprecedented high-energy scales and search for hints of new physics. Looking ahead, the continued integration of resources to fully harness these evolving technologies will enhance our efforts to deepen our understanding of the fundamental laws of nature.

关键词： high energy physics quantum sensing quantum simulations quantum machine learning quantum information

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Quantum control for time-dependent noise by inverse geometric optimization

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Science China(Physics,Mechanics & Astronomy) 2024年第9期67卷 51-57页

作者： Xiaodong Yang Yingcheng Li Ran Liu Xinfang Nie Tao Xin Dawei Lu Jun Li Institute of Quantum Precision Measurement State Key Laboratory of Radio Frequency Heterogeneous IntegrationCollege of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laboratory of Surface Physics Department of PhysicsCenter for Field Theory and Particle Physicsand Institute for Nanoelectronic Devices and Quantum ComputingFudan UniversityShanghai 200433China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area(Guangdong) Shenzhen 518045China

Quantum systems are exceedingly difficult to engineer because they are sensitive to various types of *** particular,timedependent noises are frequently encountered in experiments but how to overcome them remains a challenging *** this work,we propose a flexible robust control technique to resist time-dependent noises based on inverse geometric optimization working in the filter-function *** basic idea is to parameterize the control filter function geometrically and minimize its overlap with the noise spectral *** then effectively reduces the noise susceptibility of the controlled system *** show that the proposed method can produce high-quality robust pulses for realizing desired quantum evolutions under realistic noise ***,we demonstrate this method in examples including dynamical decoupling and quantum sensing protocols to enhance their performances.

关键词： time-dependent noise robust control quantum gates and states dynamical decoupling quantum sensing

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BPVFL: A Bidirectional Privacy-Preserving Verifiable Federated Learning Framework with Homomorphic Encryption

BPVFL: A Bidirectional Privacy-Preserving Verifiable Federat...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Liu, Jingwei Chen, Sijing Zhu, Junrong Sun, Rong Du, Xiaojiang Guizani, Mohsen Xidian University Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'an710071 China Xidian University State Key Laboratory of Isn Xi'an710071 China Stevens Institute of Technology Department of Electrical and Computer Engineering Hoboken United States Department of Machine Learning Abu Dhabi999041 United Arab Emirates

ISBN: (纸本)9798350351255

Federated learning, while advancing data privacy, faces risks of sensitive information leakage through parameter updates, making it susceptible to inference and data reconstruction attacks. Fraudulent behaviors by central servers or clients can undermine the integrity of model training, thereby reducing accuracy and affecting decision-making quality. This paper introduces a bidirectional, privacy-preserving verifiable federated learning framework(BPVFL) built on homomorphic encryption and a novel three-party zero-knowledge protocol. This framework guarantees the integrity of server aggregation and the credibility of the information uploaded by clients. Experimental results demonstrate that BPVFL effectively protects client privacy, prevents fraud by servers and certain clients, and efficiently handles numerous client disconnections with minimal overhead. © 2024 IEEE.

关键词： Federated learning

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Automatic Generation of Specification from Natural Language Based on Temporal Logic 10th

Automatic Generation of Specification from Natural Language ...

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International Workshop on Structured Object-Oriented Formal Language and Method, SOFL+MSVL 2020

作者： Wang, Xiaobing Li, Ge Li, Chunyi Zhao, Liang Shu, Xinfeng Institute of Computing Theory and Technology and ISN Laboratory Xidian University Xi’an710071 China School of Computer Science and Technology Xi’an University of Posts and Communications Xi’an710061 China

ISBN: (纸本)9783030774738

Formal specifications are usually used for describing safety system properties and play an important role in formal verification. In order to improve the effectiveness of formal specification generation and formal verification, this paper proposes a framework for automatic conversion from natural language describing properties to temporal logic formulas, and implements a tool PPTLGenerator (Propositional Projection Temporal Logic formula Generator) for the conversion. First, PPTLGenerator is developed based on JavaCC for automatic conversion from natural language to PPTL. Then, the satisfiability of a PPTL formula generated by PPTLGenerator is checked by a tool PPTLSAT. Finally, to illustrate the principle and effectiveness of the framework, a case study of the safety property of Level 3 autonomous car is provided. © 2021, Springer Nature Switzerland AG.

关键词： Formal specification

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