Systems Science Commons^™

Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang

Journal of System Simulation

Abstract: Based on the perfect performance of deep reinforcement learning (DRL) in strategy optimization, this paper proposes a strategy optimization method of action taking the multi-dimension projection action as the main research object. The method combines the simulation experiment method with the DRL method. After analyzing the current situation of strategy optimization research, the deep learning framework is selected according to the research problems, and a DRL multi-dimension projection strategy model based on the asynchronous advantage actor-critic (A3C) algorithm is constructed. Through simulation experiments, the interactive learning between the DRL model and the simulation of "out of the loop" is …

A Simulation Method Based On Multi-Source Sensors For Aircraft Type Identification, Shaozhu Gu, Yuxin Ying, Huajie Zhang, Yiqi Tong

Journal of System Simulation

Abstract: Existing simulation methods for aircraft type identification mainly focus on a single sensor and a single target. They do not consider the joint acquisition of aircraft parameters by various sensor devices such as optoelectronics, radar, and electronic detection in real scenarios, leading to the simple simulation scenarios. This paper proposes a simulation platform based on multi-source sensors. Specifically, the platform includes an infrared image simulator that uses a cycleGAN network to generate infrared images of the aircraft, a flight simulator that adopts the three-degree-of-freedom flight control method to generate the movement trajectory of the aircraft, a radar simulator, that …

Experimental Data For: "Effects Of Network Connectivity And Functional Diversity Distribution On Human Collective Ideation", Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. Maclaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama

Systems Science and Industrial Engineering Faculty Scholarship

This is the dataset collected from our online human-subject experiments described in the following manuscript:

Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, and Hiroki Sayama:
"Effects of Network Connectivity and Functional Diversity Distribution on Human Collective Ideation"
https://arxiv.org/abs/2307.04284

The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña

Social Science - All Scholarship

This work formulates the hazard prediction problem while addressing the research question: Can machine learning create a model to automatically recognize patterns that correspond to hazard state conditions during a mission-critical operation? Supervised learning models were trained and tested on data observed from mission simulators, which allowed for safe observation of dynamic system states and undesirable casualty events. The prediction task was formulated as a binary classification problem, producing the probability of being in a hazard state at time t and providing situational awareness of a possible imminent loss. Several modeling architectures were investigated: neural networks, logistic regression, a support …

Cybersecurity Awareness And Risks Among Students, Staff & Faculty At The University Of North Alabama, Jerry Lwamba

Theses

As individuals and organizations become significantly connected to the internet, cybercriminals find an increasing number of ways to exploit their targets (Broadhurst, 2018). This study explores the world of cybersecurity awareness of risks associated with online activities within the University of North Alabama (UNA). This research aims to assess the level of cybersecurity awareness of risks university stakeholders face, and to also understand behaviors that expose them to cybercrime and emphasize the urge for comprehensive cybersecurity best practices. When cybercriminals employ tactics such as spam, phishing, or spear phishing in their attempts to break into network systems, distribute malware, or …

Leveraging Redundancy As A Link Between Spreading Dynamics On And Of Networks, Felipe Xavier Costa

Electronic Theses & Dissertations (2024 - present)

A constant quest in network science has been in the development of methods to identify the most relevant components in a dynamical system solely via the interaction structure amongst its subsystems. This information allows the development of control and intervention strategies in biochemical signaling and epidemic spreading. We highlight the relevant components in heterogeneous dynamical system by their patterns of redundancy, which can connect how dynamics affect network topology and which pathways are necessary to spreading phenomena on networks. In order to measure the redundancies in a large class of empirical systems, we develop the backbone of directed networks methodology, …

A Human-Centered Framework For Oncological Healthcare System Modeling Applied To Mobile Radiation Delivery, Alex Price

Doctoral Dissertations

"Healthcare systems engineering is challenging due to the complexity, geographic expansiveness, inertial properties, and the heterogeneous sub-systems, with varying vested interests. Additionally, humans comprise many of the forms and functions, and are independent, with resistance and uncertainty in their decision-making that adds complexity. Human-centered systems modeling approaches are therefore needed to capture this unique aspect of a healthcare system and to enhance understanding of emergent healthcare properties. This dissertation focuses on integrating systems modeling within healthcare and emphasizes the importance of incorporating human decision-making. Moreover, the incorporation of a human-centered approach yields particularly valuable insights into the decision-making processes that …

Mouralherwaqh Coastal Wetland Road Crossing Da'luk, Romel Robinson Ii

Cal Poly Humboldt theses and projects

The integration of Indigenous and Western science plays an essential role in Tribally led collaborations for land management. This process of woven sciences is rooted in reciprocal relations and partnerships guided by Tribal Nations. Our cohort was invited by Wiyot Tribal Representatives to investigate a culvert located within the wetlands of Mouralherwaqh— a parcel of land reacquired by the Wiyot Tribe in 2022. This document seeks to share our experience and analysis as part of the Wiyot Tribe’s broader journey in navigating ecocultural restoration projects within Mouralherwaqh. The four community interests we investigated for the wetland crossing included a resized …

Co-Evolving Multi-Agent Transfer Reinforcement Learning Via Scenario Independent Representation, Ayesha Siddiqua

Graduate Theses/Dissertations

Multi-Agent Reinforcement Learning (MARL) addresses complex tasks involving cooperation and competition among agents, training them to develop optimal policies for collective goals. However, facilitating simultaneous learning for multiple agents is challenging because the complexity increases rapidly with the number of agents. Current methods encompass a variety of centralized, decentralized, semi-centralized, and hybrid approaches to balance the trade-offs between computational efficiency, scalability, and coordination in MARL. In this study, I employed a centralized training with semi-centralized execution (CTSCE) framework, utilize both local observations from agents and abstracted global observations to effectively train agents in cooperative environments. Additionally, earning complex, domain-specific tasks …