Artificial Intelligence

Contents The main content of the course is summarized below. Introduction to HCI and HRI Human factors and engineering design Interface design, usability evaluation, universal design, multimodal interfaces (touch, vision, natural language and 3-D audio) Virtual reality and spatial displays Embodiment and anthropomorphism Perception of human behavior Multimodal interaction HCI and HRI applications User studies and evaluation methods Ethical and social implications of HMI Associated skills Knowledge and understanding: The course offers an overview of different research topics in HCI and HRI and, more specifically, in using Artificial Intelligence techniques to model and reason about human-machine interaction tasks. Techniques for requirement collection and analysis, goal and task models, interaction and system models, multimodal and personalized interactions, methods for usability evaluation will be examined. Some advanced issues in HCI and HRI, such as cooperative systems, immersive and ubiquitous environments, intelligent interfaces, social interactions, etc., will also be addressed. The topics are covered by researchers in the field who will introduce the student to research problems and recent and relevant applications in HCI, HRI and AI. Applied knowledge and understanding: The course provides the knowledge necessary to undertake research work in these fields using practical tools for experimental validation, including understanding the concepts of HMI and usability, conducting a research project of an interactive interactive system following the UCD methodology, and reporting the results according to scientific standards. Critical and judgment skills: The course proposes advanced methods to study, understand and apply results reported on scientific articles, and integrate these results to create innovative HCI, HRI and AI applications. The student learns how to use results from the literature as a basis for new research and how to evaluate the usability of an interactive system and its adequacy with respect to the goals and tasks of end users and stakeholders. Communication skills: Group activities in the classroom and the need to make presentations to the class allow the student to develop the ability to communicate and share the knowledge acquired and to compare themselves with others on the topics of the course. In particular, the project activities and the course homeworks allow the student to be able to collaborate in the design and development of an interactive system. Learning ability: In addition to the classic learning skills provided by the theoretical study of the teaching material, the course develops methods to stimulate the student to deepen his knowledge of some of the topics she presents to the course and to the work group. Furthermore the course stimulates the student to effectively apply both the concepts and the techniques learned during the course in homeworks and in a research project. Learning outcomes Understand motivations, opportunities and limits of HMI applications Identify the appropriate models and algorithms to solve a specific HMI problem Evaluate the performance of HMI systems Present the result of an HMI study according to scientific standards. Describe limitations of a given HMI solution Organize and conduct an oral presentation of a research paper Develop a research project in HMI and AI and present the results