Human-in-the-Loop Simulations is a compilation of articles from experts in the design, development, and use of human-in-the-loop simulations. The first section of the handbook consists of papers on fundamental concepts in human-in-the-loop simulations, such as object-oriented simulation development, interface design and development, and performance measurement. The second section includes papers from researchers who utilized HITL simulations to inform models of cognitive processes to include decision making and metacognition. The last section describes human-in-the-loop processes for complex simulation models in trade space exploration and epidemiological analyses. Human-in-the-Loop Simulations is a useful tool for multiple audiences, including graduate students and researchers in engineering and computer science.

Human-in-the-Loop Simulations is a compilation of articles from experts in the design, development, and use of human-in-the-loop simulations. The first section of the handbook consists of papers on fundamental concepts in human-in-the-loop simulations, such as object-oriented simulation development, interface design and development, and performance measurement. The second section includes papers from researchers who utilized HITL simulations to inform models of cognitive processes to include decision making and metacognition. The last section describes human-in-the-loop processes for complex simulation models in trade space exploration and epidemiological analyses. Human-in-the-Loop Simulations is a useful tool for multiple audiences, including graduate students and researchers in engineering and computer science.

Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.

This easy to read text provides a broad introduction to the fundamental concepts of modeling and simulation (M&S) and systems engineering, highlighting how M&S is used across the entire systems engineering lifecycle. Features: reviews the full breadth of technologies, methodologies and uses of M&S, rather than just focusing on a specific aspect of the field; presents contributions from specialists in each topic covered; introduces the foundational elements and processes that serve as the groundwork for understanding M&S; explores common methods and methodologies used in M&S; discusses how best to design and execute experiments, covering the use of Monte Carlo techniques, surrogate modeling and distributed simulation; explores the use of M&S throughout the systems development lifecycle, describing a number of methods, techniques, and tools available to support systems engineering processes; provides a selection of case studies illustrating the use of M&S in systems engineering across a variety of domains.

Simulation and molding are efficient techniques that can aid the city and regional planners and engineers in optimizing the operation of urban systems such as traffic light control, highway toll automation, consensus building, public safety, and environmental protection. When modeling transportation systems such as freeway systems, arterial or downtown grid systems, the city planner and engineer is concerned with capturing the varied interactions between drivers, automobiles, and the infrastructure. Modeling and simulation are used to effectively optimize the design and operation of all of these urban systems. It is possible that in an urban simulation community workshop, citizens can work interactively in front of computers and be able using the click of the mouse to walk up to their own front porch, looking at the proposed shopping mall alternatives across the street from virtually any angle and proposed bridge or tunnel and see how it can reduce traffic congestion. Buildings can be scaled down or taken out, their orientation can be changed in order to check the view and orientation in order to have better site with efficient energy-conservation. The stone or brick material on a building can be replaced by colored concrete, or more trees and lampposts can be placed on the site. Such flexibility in simulation and animation allows creative ideas in the design and orientation of urban sites to be demonstrated to citizens and decision makers before final realization.

Simulations are frequently used techniques for training, performance assessment, and prediction of future outcomes. In this thesis, the term “human-centered simulation” is used to refer to any simulation in which humans and human cognition are integral to the simulation’s function and purpose (e.g., simulation-based training). A general problem for human-centered simulations is to capture the cognitive processes and activities of the target situation (i.e., the real world task) and recreate them accurately in the simulation. The prevalent view within the simulation research community is that cognition is internal, decontextualized computational processes of individuals. However, contemporary theories of cognition emphasize the importance of the external environment, use of tools, as well as social and cultural factors in cognitive practice. Consequently, there is a need for research on how such contemporary perspectives can be used to describe human-centered simulations, re-interpret theoretical constructs of such simulations, and direct how simulations should be modeled, designed, and evaluated. This thesis adopts distributed cognition as a framework for studying human-centered simulations. Training and assessment of emergency medical management in a Swedish context using the Emergo Train System (ETS) simulator was adopted as a case study. ETS simulations were studied and analyzed using the distributed cognition for teamwork (DiCoT) methodology with the goal of understanding, evaluating, and testing the validity of the ETS simulator. Moreover, to explore distributed cognition as a basis for simulator design, a digital re-design of ETS (DIGEMERGO) was developed based on the DiCoT analysis. The aim of the DIGEMERGO system was to retain core distributed cognitive features of ETS, to increase validity, outcome reliability, and to provide a digital platform for emergency medical studies. DIGEMERGO was evaluated in three separate studies; first, a usefulness, usability, and facevalidation study that involved subject-matter-experts; second, a comparative validation study using an expert-novice group comparison; and finally, a transfer of training study based on self-efficacy and management performance. Overall, the results showed that DIGEMERGO was perceived as a useful, immersive, and promising simulator – with mixed evidence for validity – that demonstrated increased general self-efficacy and management performance following simulation exercises. This thesis demonstrates that distributed cognition, using DiCoT, is a useful framework for understanding, designing and evaluating simulated environments. In addition, the thesis conceptualizes and re-interprets central constructs of human-centered simulation in terms of distributed cognition. In doing so, the thesis shows how distributed cognitive processes relate to validity, fidelity, functionality, and usefulness of human-centered simulations. This thesis thus provides a new understanding of human-centered simulations that is grounded in distributed cognition theory.

This volume is based on papers accepted for the Second International Workshop on Multi-agent-based Simulation (MABS-2000)federated with the Fourth Int- national Conference on Multi Agent Systems (ICMAS-2000)held in Boston in July 2000. The purpose of MABS-2000 was to investigate and develop the synergy - tween software engineering for multi-agent systems and agent-based social s- ulation. The papers included in the MABS-2000 workshop were selected either because they explore how agent interaction can be used to build multi-agent s- tems or they o?er examples of problem-oriented (rather than technique-oriented) systems. No paper was selected if it speci?ed a model or an issue to make it ?t a previously chosen technique. All of the papers in the volume have been reviewed and in many cases revised since the workshop. Two papers (by Edmonds and by Hales)as well as the editorial introduction have been added to those accepted for the workshop. As editors and workshop organisers, we are very grateful to the participants who engaged enthusiastically in the discussions about both individual papers and the issues facing the MABS community. Issues raised and positions taken in those discussions are reported in the editorial introduction. We are also grateful to the authors for their punctuality and the grace with which they received and responded to editorial comments and requests. Klaus Fischer, the ICMAS-2000 workshops chair, was exceptionally patient and diplomatic in reconciling our demands with the resources available.