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Articles 91 - 120 of 310
Full-Text Articles in Systems Science
Control Strategy For Uav Cluster Formation Rendezvous Based On Lde-Maddpg Algorithm, Wei Xiao, Jiabo Gao, Xueliang Ke
Control Strategy For Uav Cluster Formation Rendezvous Based On Lde-Maddpg Algorithm, Wei Xiao, Jiabo Gao, Xueliang Ke
Journal of System Simulation
Abstract: To solve the problem of difficulty in UAV cluster formation rendezvous based on MADDPG algorithm, an autonomous collaborative control strategy based on LDE-MADDPG algorithm is proposed. To address the issues of weak generalization, poor scalability, and slow cluster training process of MADDPG algorithm, LDE-MADDPG algorithm was proposed by designing a state feature learning network and a decoupled Critical network. By integrating LDE-MADDPG algorithm with strategy generation elements such as the decoupled reward function, cluster state space, and UAV action space, a control strategy for UAV cluster formation endezvous that can adapt to diverse formations and varying quantities has been …
Robot Path Planning Based On Improved A-Ddqn Algorithm, Peilong Ni, Pengjun Mao, Ning Wang, Mengjie Yang
Robot Path Planning Based On Improved A-Ddqn Algorithm, Peilong Ni, Pengjun Mao, Ning Wang, Mengjie Yang
Journal of System Simulation
Abstract: An improved A-DDQN algorithm is proposed to address the challenges of reward sparsity and the inability to distinguish sample importance in traditional DQN algorithms during robot path planning. Building on the original DQN, an enhancement is made by incorporating the Double-DQN approach, which updates the predictive Q-value network based on actions selected by the Q network, rather than directly using the predicted Q-values for action selection, thereby mitigating overestimation issues. Secondly, the concept of artificial potential field (APF) is introduced to design specific rewards for each step of the robot's movement, guiding the robot and addressing the problem of …
From Model To Behavior: Methodological Challenges In Using Fuzzy Cognitive Maps To Represent Mental Models, Catherine Elizabeth Moore
From Model To Behavior: Methodological Challenges In Using Fuzzy Cognitive Maps To Represent Mental Models, Catherine Elizabeth Moore
Dissertations and Theses
This dissertation examines the use of Fuzzy cognitive maps (FCMs) as representations of mental models and how these representations connect to individual behavior. Fuzzy cognitive maps (FCMs) are semi-quantitative models that encode cause-and-effect structures as directed graphs. They are frequently used to represent individuals' knowledge structures/mental models and should in theory correlate to actions and decisions of individuals; however, this correlation has yet to be explored in a systematic manner. This dissertation represents the first step in experimental research on the connection between FCMs and individual behavior. It examines two theories of how humans use mental models, one based on …
Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian
Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian
Publications
A crucial aspect of quality control for Additive Manufacturing (AM) processes is the acquisition of diverse data from the entire lifecycle of the product. AM data has grown significantly in terms of diversity and volumes, resulting in diverse data formats of increasing volumes, including time series, images, and point clouds. Large quantities of these data are essential for effective in-situ process monitoring and ex-situ non-destructive evaluation. However, this will result in large manufacturing and inspection datasets that are difficult to manage for users, which will delay the broader adoption of AM for mission critical applications. This motivates the urgent need …
The Utilisation Of The Fourth Industrial Revolution (4ir) Technologies In E-Government Service Delivery: A Systematic Literature Review, Arnet Zitha, Noluntu Mpekoa, Sheethal Tom
The Utilisation Of The Fourth Industrial Revolution (4ir) Technologies In E-Government Service Delivery: A Systematic Literature Review, Arnet Zitha, Noluntu Mpekoa, Sheethal Tom
African Conference on Information Systems and Technology
The integration of Fourth Industrial Revolution (4IR) technologies is transforming e-Government by boosting citizen engagement and enhancing service efficiency. However, gaps still exist in understanding the various applications, impacts, and barriers to adoption. This systematic review synthesises literature from 16 studies published between 2017 and 2025, illustrating how technologies like blockchain, artificial intelligence, big data, Internet of Things, and machine learning are employed and their effects on e-Government service delivery. The review reveals that 4IR technologies continue to play a vital role in e-Government services by addressing security threats, simplifying verification and authentication, building trust, and improving the quality and …
An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki
An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki
Doctoral Dissertations
The Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are revolutionizing critical infrastructures, but their expansion has also introduced severe cybersecurity vulnerabilities. Traditional IoT Bot Detection Systems (IBDS) struggle to scale in environments characterized by high-dimensional, large-scale, and redundant network traffic. These challenges hinder the development of reliable cloud-based intrusion detection systems. The limitations of static and rulebased methods in detecting evolving IoT botnet attacks—such as those launched by Mirai and Gafgyt—underscore the need for intelligent, adaptive approaches. To address this, the present study proposes a machine learning and deep learning-driven IoT Botnet Detection Model, validated through …
Detection Of Small Apple Targets Based On Improved Yolov5 In Natural Environments, Zilong Liu, Lei Zhang
Detection Of Small Apple Targets Based On Improved Yolov5 In Natural Environments, Zilong Liu, Lei Zhang
Journal of System Simulation
Abstract: The distribution of apples usually features occlusion and small and dense targets. To address these issues, a target detection algorithm was proposed based on an improved YOLOv5 model. Specifically, this paper added the coordinate attention (CA) mechanism, receptive field block (RFB), and adaptively spatial feature fusion (ASFF) modules to the YOLOv5, enhancing the ability to detect small targets. Additionally, the proposed algorithm replaced the CIoU in YOLOv5 with SIoU to improve the target detection box's prediction accuracy. Finally, some normal convolutions were replaced with depthwise separable convolutions (DSC), effectively reducing the calculation burden. Experiment results show that the comprehensive …
Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren
Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren
Journal of System Simulation
Abstract: Traditional scene generation methods for maritime target recognition consider only the effects of different environments on the generated scene data, while overlooking the changes in scene information caused by sensor detection parameters, resulting in a lack of accuracy and authenticity in generated scenes. To address this issue, a detection parameter-based scene generation method for maritime target recognition was proposed. For the task of maritime target recognition, key detection parameters affecting scene generation quality and essential scene features were analyzed. An association relationship modeling method based on Bayesian networks was proposed to construct a mapping relationship model between scene features …
Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang
Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang
Journal of System Simulation
Abstract: A multi-source information fusion approach based on the dempster-shafer (D-S) evidence theory with a fuzzy reward-penalty mechanism was proposed to address the issues of underreporting and false reporting in the early prediction of ship fires. PyroSim was utilized to construct a ship's laboratory model for fire simulation. Variations in carbon monoxide, temperature, and smoke concentration were recorded for data acquisition, followed by the application of a sigmf function for membership assignment. By leveraging the classical D-S theory, a reward-penalty mechanism was applied in weighted evidence fusion. Reward-penalty factors were utilized to differentiate various basic probability assignments, with unified belief …
Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng
Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng
Journal of System Simulation
Abstract: The preliminary design of the overall operation performance of diesel engines cannot be guided by actual vehicle driving tests, which hinders the improvement of the power development level and efficiency of special vehicles. By using the virtual visual simulation engine Unity3D, two virtual driving scenario models were established: a flat road scenario and an undulating road scenario. Based on the speed characteristic parameters of the engine, a diesel engine's operation performance output model was constructed. Combined with the transmission system model and the longitudinal dynamics model of the vehicle's center of mass, a straight vehicle driving dynamics model was …
Simulation And Optimization Of Support Processes For Aircraft Fleet Launch Under Limited Resources, Feng Gong, Tao Jiang, Qin Zhang, Yu Liu
Simulation And Optimization Of Support Processes For Aircraft Fleet Launch Under Limited Resources, Feng Gong, Tao Jiang, Qin Zhang, Yu Liu
Journal of System Simulation
Abstract: To address the scheduling problem of aircraft fleet support processes under limited resources, a fleet support process optimization model that covered multiple aircraft, activities, and resource constraints was developed. An activity node graph model was used to establish the temporal logic, resource competition, and other constraints in the fleet support process, forming a "time – activity – resource" multidimensional optimization model. A genetic algorithm based on priority encoding was proposed, incorporating a serial decoding strategy and a dynamic penalty function to handle the complex constraints in the model, efficiently solving the optimization problem under complicated temporal and resource constraints. …
Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei
Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei
Journal of System Simulation
Abstract: In order to improve the accuracy of load forecasting and fully extract the hidden relationships between load and other characteristic factors, a load forecasting method based on dual-attention temporal convolutional LSTM network (DA-TCLSNet) was proposed. Correlation analysis was conducted on the dataset using the maximum information coefficient method to perform feature screening to reduce the computational cost of the model. The model input was constructed using a sliding window. The DATCLSNet forecasting model was constructed. The temporal convolutional layer extracted dependencies at different time scales and captured the nonlinear characteristics among variables such as load and weather. The multi-head …
Research On 3d Visualization Of Safety Monitoring And Early Warning For Steel Continuous Casting Scenarios, Wei Zhang, Wei Sheng, Yidan Cao, Tingsheng Zhao
Research On 3d Visualization Of Safety Monitoring And Early Warning For Steel Continuous Casting Scenarios, Wei Zhang, Wei Sheng, Yidan Cao, Tingsheng Zhao
Journal of System Simulation
Abstract: In order to improve the visualization and integration of production safety monitoring and fault warning, a three-dimensional (3D) visualization model architecture for whole-process industrial production safety monitoring and early warning for steel continuous casting scenarios was designed. By using 3ds Max and Unity3D, a multi-dimensional and multi-scale model was built, and functional modules such as visualization display and multi-level early warning for safety monitoring data were developed. By combining WebGL technology and Node. js runtime environment, the visualization of whole-process industrial production safety monitoring based on Web terminal was realized. The alarm threshold determination method for whole-process industrial production …
Optimal Scheduling Of An Integrated Energy System Considering Demand Response And Two-Stage P2g, Xinhui Duan, Zelong Cheng, Dongchao Zhang, Xiaochong Duan
Optimal Scheduling Of An Integrated Energy System Considering Demand Response And Two-Stage P2g, Xinhui Duan, Zelong Cheng, Dongchao Zhang, Xiaochong Duan
Journal of System Simulation
Abstract: In the context of carbon peaking and carbon neutrality goals, this study aims to improve the energy utilization rate and further explore the role of user-side flexible loads and P2G equipment in energy saving and emission reduction. An optimal scheduling model for integrated energy systems considering demand response and two-stage P2G was proposed. A regional integrated energy system coupled with electricity, heating, cooling, gas, storage, and hydrogen was taken as the research object. Models for system equipment and two-stage P2G were established. Based on load characteristics, a multi-load demand response model for electricity, heating, and cooling was constructed using …
Storage Life Assessment Methods For Long-Term Storage Products Based On Multi-Scale Simulation: A Review, Hongmin Li, Xiao Han, Shuo Huang, Shengpeng Zhang, Shuanglong Rong, Hao Li, Cheng Qian
Storage Life Assessment Methods For Long-Term Storage Products Based On Multi-Scale Simulation: A Review, Hongmin Li, Xiao Han, Shuo Huang, Shengpeng Zhang, Shuanglong Rong, Hao Li, Cheng Qian
Journal of System Simulation
Abstract: Traditional experiment-based life assessment methods for long-term storage products suffer from drawbacks such as prolonged duration, high cost, and low prediction accuracy, greatly limiting the effectiveness of storage life assessment in practical applications. With the advancement of digital simulation technology, simulation analysis methods based on the physics of failure (PoF) have emerged as a research hotspot in the field of storage life assessment, as they can accurately characterize product aging behavior. The multi-scale characteristics of long-term storage products and their typical storage failure modes and mechanisms were analyzed. Multi-scale modeling and simulation analysis methods for storage failures of fundamental …
Research On Digital Simulation Method For Cognitive Load Evaluation Of Pilots, Zeng Fan, Mingjun He, Xiangyu Xing
Research On Digital Simulation Method For Cognitive Load Evaluation Of Pilots, Zeng Fan, Mingjun He, Xiangyu Xing
Journal of System Simulation
Abstract: The operator's cognitive load constitutes a critical determinant of task performance. Pilots, as the primary operators of aircraft, must face an overwhelming volume of information during complex missions, which significantly heightens the risk of cognitive overload and operational errors. Evaluating cognitive load during tasks helps reduce human errors and improve system safety by optimizing design schemes. A simulation model was established to dynamically predict the pilots' cognitive load during tasks for multi-task scenarios. Based on the multiple resource theory, a method for quantifying cognitive load in multi-task conditions was established. By considering cognitive capacity, task time constraints, task priority, …
Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng
Digital Testing And Evaluation: Current Status, Challenges, And Prospects, Bo Sun, Kai Zheng
Journal of System Simulation
Abstract: Digital testing and evaluation (DTE) represents a novel paradigm in the evolution of testing and evaluation methodologies within the digital era. It is achieved through the integration of multiple digital theories and technologies to conduct testing and evaluations in the digital domain. This paper analyzed the characteristics of test objects across different historical periods, reviewed the core features of testing and evaluation techniques in each stage, and unveiled the paradigm shifts within the testing and evaluation technology system. Building upon this foundation, it explored the new demands placed on testing by test objects in the information age, clarifying the …
Dynamic Testing Architecture Of Intelligent Unmanned Systems Based On Parallel Battlefields, Dayong Liu, Zhiming Dong, Qisheng Guo, Wenjun Zhang, Jiancheng Gao
Dynamic Testing Architecture Of Intelligent Unmanned Systems Based On Parallel Battlefields, Dayong Liu, Zhiming Dong, Qisheng Guo, Wenjun Zhang, Jiancheng Gao
Journal of System Simulation
Abstract: To improve the inadequacy of traditional test and identification systems, this paper proposed an overall architecture for dynamic testing across the entire lifecycle based on the concept of parallel battlefield (integration of physical, virtual, and cognitive battlefields), meeting the new requirements for the testing of intelligent unmanned systems. This architecture included high-fidelity mapping between virtual and physical battlefields, red-blue adversarial deductions and model optimization, simulation to reality (Sim2Real), human-machine collaboration, and cloud-end integrated control, as well as multidimensional assessment and confidence analysis. Centered on the principles of "mutual driving between virtual and physical battlefields, dynamic closed-loop, human-machine collaboration, and …
Adaptive Sampling And Ghost Multi-Scale Fusion For Lightweight Weld Defect Detection, Bin Lu, Xuan Yang, Zhenyu Yang, Xiaotian Gao
Adaptive Sampling And Ghost Multi-Scale Fusion For Lightweight Weld Defect Detection, Bin Lu, Xuan Yang, Zhenyu Yang, Xiaotian Gao
Journal of System Simulation
Abstract: To improve the accuracy and speed of welding defect detection and achieve lightweight models, a lightweight weld defect detection network based on YOLOv8, named light adaptive-weight sampling-YOLO (LAW-YOLO), was proposed. A lightweight adaptive weight sampling LAWS module was designed. It constructed an adaptive weight attention feature map by learning the interacting features within the receptive field. An optimized efficient weighted bidirectional feature pyramid network was adopted as the feature extraction backbone in LAW-YOLO. Furthermore, a ghost multi-scale sampling module was designed, and a hybrid attention mechanism was introduced to enhance the detection capability for small-scale defect targets. Experimental results …
Optimization Of Product Oil Distribution With Multiple Trips And Multiple Due Dates Under Dynamic Demand, Yong Xie, Hailong Gao, Yutao Chen, Huanjiang Wang
Optimization Of Product Oil Distribution With Multiple Trips And Multiple Due Dates Under Dynamic Demand, Yong Xie, Hailong Gao, Yutao Chen, Huanjiang Wang
Journal of System Simulation
Abstract: In the case of dynamic demand, considering the order due date, vehicle transportation time window, and other factors, this paper developed an optimization model of periodic product oil distribution with multiple trips and multiple due dates to maximize the distribution revenue. The paper also designed a reinforcement learning-based large neighborhood search algorithm to solve the problem. The initial solution was constructed based on the forward insertion heuristic algorithm. Then, a deep reinforcement learning model for neighborhood operator selection was designed. By fitting the action value function through the double deep Q network, the optimal neighborhood operator was selected, and …
Resource Allocation Method For Virus Spreading Control Based On Multi-Granularity Cooperative Coevolution, Xuanli Shi, Weineng Chen, An Song, Tianfang Zhao
Resource Allocation Method For Virus Spreading Control Based On Multi-Granularity Cooperative Coevolution, Xuanli Shi, Weineng Chen, An Song, Tianfang Zhao
Journal of System Simulation
Abstract: According to the principle of simplifying a complex problem into sub-problems for solution, a resource allocation method for virus spreading control based on multi-granularity cooperative coevolution (MGCC) was proposed. According to the characteristics of human's social network structures, MGCC decomposed the network into sub-networks with different scales according to different decomposition granularities. A contribution-based decomposition granularity selection strategy was proposed. Historical archives were used to record the contribution of different decomposition granularities to optimization, and the appropriate decomposition granularity was selected according to the optimization status. A projection-based constraint repairing strategy was designed to ensure the feasibility of solutions. …
Research On Simulation Technology Of Fire Extinguishing In Engine Compartment Of Special Vehicle, Jianmin Niu, Yue Zhong, Feng Xu, Jindun Ma
Research On Simulation Technology Of Fire Extinguishing In Engine Compartment Of Special Vehicle, Jianmin Niu, Yue Zhong, Feng Xu, Jindun Ma
Journal of System Simulation
Abstract: In view of the difficulty of measuring the detection response time and evaluating fire extinguishing abilities of the fire extinguishing system after a fire accident in the engine compartment, the turbulence model was adopted, and numerical modeling of the fire propagation and the diffusion process of Halon fire extinguishing agent during the firefighting process was carried out. The development of fire and the fire extinguishing process at the corner and the middle position of the vehicle compartment was simulated, and the temperature changes during the occurrence and extinguishing of fires in different environments were collected, so as to obtain …
Study On Semi-Physical Simulation Method Of Air Turbo Rocket Engine In Startup Process, Xuesen Yang, Wei Zhao, Binglong Zhang, Sanqun Ren, Xiaorong Xiang, Qingjun Zhao
Study On Semi-Physical Simulation Method Of Air Turbo Rocket Engine In Startup Process, Xuesen Yang, Wei Zhao, Binglong Zhang, Sanqun Ren, Xiaorong Xiang, Qingjun Zhao
Journal of System Simulation
Abstract: To satisfy the requirements for validating the control law of air turbo rocket (ATR) engines, a semi-physical simulation approach was proposed based on serial communication. This platform integrated a rapid prototype system, a supply system, a measurement and control system, a signal simulator, a fault injection system, and a real-time computer. A digital model of the engine was developed based on cross-compilation technology, enabling the coupling and semi-physical simulation of the engine control system and the supply system. A semi-physical simulation of the ATR engine in the startup process was carried out, and the fault handling strategy of the …
Trajectory Planning And Tracking For Multi-Quadcopter In Dynamic Obstacle Environments, Haosheng Jiang, Fangfang Wu, Zexian Huang, Ziyue Ma, Chunyun Dong, Xubin Ping
Trajectory Planning And Tracking For Multi-Quadcopter In Dynamic Obstacle Environments, Haosheng Jiang, Fangfang Wu, Zexian Huang, Ziyue Ma, Chunyun Dong, Xubin Ping
Journal of System Simulation
Abstract: Multi-quadrotor UAV systems face challenges when performing complex tasks in dynamic obstacle environments. Therefore, a comprehensive particle swarm optimization-based task allocation method, a trajectory planning integrating the traditional Informed-RRT* and A* algorithms, and a trajectory tracking method based on model predictive control were designed. The multi-quadrotor task allocation problem was constructed as a classical multiple traveling salesman problem, and then, the particle swarm optimization was used to assign the task to multi-quadrotor UAVs. A fusion algorithm that combined the advantages of traditional Informed-RRT* and A* algorithms for quadrotor UAV trajectory planning was designed, so as to ensure that a …
Multi-Robot Hierarchical Collaborative K-Robust Path Planning For Path Interference, Kaixiang Zhang, Jianlin Mao, Niya Wang, Zhihao Xu
Multi-Robot Hierarchical Collaborative K-Robust Path Planning For Path Interference, Kaixiang Zhang, Jianlin Mao, Niya Wang, Zhihao Xu
Journal of System Simulation
Abstract: To plan collision-free paths for multiple robots in interference environments, based on the multi-robot k-robust path planning, this paper designed a multi-robot hierarchical collaborative k-robust path planning framework. In the priority optimization layer, in response to the starting predicament caused by the solution sequence, the multi-robot path solving sequence was determined based on the closure factor. In the multi-robot robust coordination layer, with the goal of improving solution efficiency, a safety interval was introduced as the basis for the design of k-robustness and collision-free avoidance. A collision-free path constraint for multiple robots in the sense of k-robustness was given. …
Research On Non-Singular Fast Integral Terminal Sliding Mode Trajectory Tracking Control Of Six-Axis Robotic Arm, Tao Chen, Lizhong Wang, Xiangjun Zou, Xiaojuan Li
Research On Non-Singular Fast Integral Terminal Sliding Mode Trajectory Tracking Control Of Six-Axis Robotic Arm, Tao Chen, Lizhong Wang, Xiangjun Zou, Xiaojuan Li
Journal of System Simulation
Abstract: To address the trajectory tracking control challenges caused by modeling parameter inaccuracies and disturbance uncertainties in robotic arms, a non-singular fast integral terminal sliding mode control scheme was developed. A new type of non-singular fast integral terminal sliding mode controller was designed. The non-singular fast terminal sliding mode ensured the rapid convergence of the system while avoiding the singularity during convergence. The integral term was used to enhance the suppression ability of disturbances and ensure the rapid response of the controller to errors. Lyapunov stability theory was applied to analyze the controller's convergence. The simulation results show that the …
Lightweight Driver Face Object Detection Algorithm Based On Yolov8-Df, Mingyu Li, Jiaquan Lin
Lightweight Driver Face Object Detection Algorithm Based On Yolov8-Df, Mingyu Li, Jiaquan Lin
Journal of System Simulation
Abstract: The YOLOv8n detection algorithm has a large amount of computation and parameters in the driving environment. To address this issue, a lightweight driver facial object detection algorithm YOLOv8-DF was proposed. A lightweight multi-scale convolution module (LMCM) was proposed to replace the Conv module in the network, and the dual-channel design could reduce the computation and parameter quantity of the algorithm; the multi-scale design could enrich the feature information inside the network. The lightweight convolutional GhostConv, Fasterblock module, and C2f module were fused, and a dual-channel lightweight convolution module (DLCM) was fused with the SPPF module. The experimental results show …
A Control Theoretic Approach To The Stochastic Multi-Armed Bandit Problem With Applications In Hyperparameter Optimization, Jonathan Gornet
A Control Theoretic Approach To The Stochastic Multi-Armed Bandit Problem With Applications In Hyperparameter Optimization, Jonathan Gornet
McKelvey School of Engineering Graduate Student Theses & Dissertations
Decision-making under uncertainty is a fundamental problem encountered frequently in many real-world applications. This challenge has been rigorously formulated as the Stochastic Multi-Armed Bandit (SMAB) problem, which consists of a learner interacting with an environment. For each interaction, the learner selects an action and then receives a reward from the environment based on the chosen action. The learner's objective is to maximize the accumulated reward over a set number of rounds. This thesis addresses the SMAB problem by leveraging the field of Control Theory and dynamical systems. We specifically focus on a SMAB environment where the rewards are the output …
Moment Ensemble Approaches For Estimation And Robust Quantum Control, Andre Luiz Paes De Lima
Moment Ensemble Approaches For Estimation And Robust Quantum Control, Andre Luiz Paes De Lima
McKelvey School of Engineering Graduate Student Theses & Dissertations
Large-scale population dynamics governed by ensemble systems present significant challenges due to their inherently high dimensionality. Recent advances have demonstrated the effectiveness of moment-based methods (particularly those employing polynomial bases such as Legendre and Chebyshev polynomials) when integrated with optimization techniques for control design in ensemble systems. However, these methods have not been extensively explored for enhancing robustness against systematic noise, nor have they been widely applied to complex quantum systems involving multi-parameter configurations and entanglement phenomena. In this work, we extend the application of moment methods in ensemble systems through two projects. Initially by developing a Kalman filter analogue, …
Emergence Of Norms In The Presence Of Social Network Structure In A Stochastic Evolutionary Game Theory Model, Parker Foresman
Emergence Of Norms In The Presence Of Social Network Structure In A Stochastic Evolutionary Game Theory Model, Parker Foresman
Dissertations and Theses
In their 2000 paper, The Emergence of Classes in a Multi-Agent Bargaining Model, Axtell, Epstein, and Young introduced an agent-based bargaining model to study how social norms can emerge and persist from the decentralized, asynchronous interactions of individual agents in the presence of noise, even when these agents have no predefined preferences or advantages. This thesis extends their model by incorporating structured interaction networks, allowing us to investigate how the topology of agent interactions influences long-run dynamics and norm formation. Using a custom simulation package built in the Julia programming language, we replicate the original results under a complete …