This book presents cutting-edge research on innovative human systems integration and human–machine interaction, with an emphasis on artificial intelligence and automation, as well as computational modeling and simulation. It covers a wide range of applications in the area of design, construction and operation of products, systems and services. The book describes advanced methodologies and tools for evaluating and improving interface usability, new models, and case studies and best practices in virtual, augmented and mixed reality systems, with a special focus on dynamic environments. It also discusses various factors concerning the human user, hardware, and artificial intelligence software. Based on the proceedings of the 4th International Conference on Intelligent Human Systems Integration (IHSI 2021), held on February 22–24, 2021, the book also examines the forces that are currently shaping the nature of computing and cognitive systems, such as the need to reduce hardware costs; theimportance of infusing intelligence and automation; the trend toward hardware miniaturization and optimization; the need for a better assimilation of computation in the environment; and social concerns regarding access to computers and systems for people with special needs. It offers a timely survey and a practice-oriented reference guide for policy- and decision-makers, human factors engineers, systems developers and users alike.
Daftar Isi
Anticipating Human Decision for an Optimal Teaming between Manned and Unmanned Systems.- Delegation in Human-agent Teaming: Progress, Challenges and Prospects.- Human-Centered Design in an Automated World.- Sensor Fusion-Based Supervised Learning Approach to Collaborative Manipulation with Variable Autonomy.- Towards a Balanced Analysis for a more intelligent Human Systems Integration.- Multi-Agent Collaboration in an Adversarial Turret Reconnaissance Task.- Comparison of a Logistic and Support Vector Machine Model to Detect Discomfort in Automated Driving.- Evaluation of Swarm Supervision Complexity.- Psychophysics-Based Cognitive Reinforcement Learning to Optimize Human-Robot Interaction in Power-Assisted Object Manipulation.
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