Title Bayesian methods for interaction and design / edited by John H. Williamson, University of Glasgow, Antti Oulasvirta, Aalto University, Per Ola Kristensson, University of Cambridge, Nikola Banovic, University of Michigan-Ann Arbor

Published Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2022 ©2022

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Description 1 online resource (xii, 360 pages) : illustrations Contents Cover -- Half-title -- Title page -- Copyright information -- Contents -- List of Contributors -- Preface -- Part I Introduction to Bayesian Methods -- 1 An Introduction to Bayesian Methods for Interaction Design -- 2 Bayesian Statistics -- Part II Probabilistic Interfaces and Inference of Intent -- 3 Bayesian Information Gain to Design Interaction -- 4 Bayesian Command Selection -- 5 Probabilistic UI Representation and Reasoning in Touch Interfaces -- 6 Statistical Keyboard Decoding -- 7 Human-Computer Interaction Design and Inverse Problems Part III Bayesian Optimisation in Interaction Design -- 8 Preferential Bayesian Optimisation for Visual Design -- 9 Bayesian Optimisation of Interface Features -- Part IV Bayesian Cognitive Modelling -- 10 Cue Integration in Input Performance -- 11 Bayesian Parameter Inference for Cognitive Simulators -- Appendix: Mathematical Background and Notation Summary "Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications of Bayesian modelling, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesian optimisation; and Bayesian approaches to modelling the cognitive processes of users. "-- Provided by publisher Bibliography Includes bibliographical references Notes Description based on online resource; title from digital title page (viewed on August 24, 2022) Subject Human-machine systems -- Mathematical models Human engineering -- Mathematics User interfaces (Computer systems) Bayesian statistical decision theory. COMPUTERS / Social Aspects. Bayesian statistical decision theory. Human-machine systems -- Mathematical models. User interfaces (Computer systems) Form Electronic book Author Williamson, John H., 1980- editor. Oulasvirta, Antti, 1979- editor. Kristensson, Per Ola, editor. Banovic, Nikola, 1982- editor. LC no. 2022016992 ISBN 9781108874830 1108874835

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