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E-raamat: Intelligent Adaptive Systems: An Interaction-Centered Design Perspective

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  • Formaat: 331 pages
  • Ilmumisaeg: 30-Oct-2018
  • Kirjastus: CRC Press Inc
  • Keel: eng
  • ISBN-13: 9781351231015
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Intelligent Adaptive Systems: An Interaction-Centered Design PerspectiveSuurem pilt
  • Formaat: 331 pages
  • Ilmumisaeg: 30-Oct-2018
  • Kirjastus: CRC Press Inc
  • Keel: eng
  • ISBN-13: 9781351231015
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"Preface When a project authority writes a request for a proposal to scope out systems design activities for achieving envisioned system goals, what systems design approaches should be requested in the statement of work? When systems designers respond tothis request, what analytical techniques and design methodologies should they propose to identify the detailed design requirements and associated constraints that will allow them to further the design? When the required information is available for the design, what implementation and evaluation methods should design engineers follow? These are common, critical questions that many project authorities, systems designers, and design engineers must address in their day-to-day jobs. Answering these questions is not easy, as many different systems design theories, analytical techniques, and design methods are available in various application domains. It is especially difficult when considering the advance of modern technologies, such as robotics, artificial intelligence, cloud-based computing, and social media technologies. As more and more intelligent and adaptive systems surround us in our daily lives, it is increasingly important that systems designers incorporate knowledge of human capabilities and limitations into new designs. For example, in today's digital age, the amount of accessible information continues to increase dramatically. Intelligent adaptive systems (IASs) offer opportunities to tailor and manage the deluge of information in an interaction-centered way. Responsive and context-sensitive design is the most promising solution to the overwhelming amounts of data we face in our daily working and personal lives"--

A synthesis of recent research and developments on intelligent adaptive systems from the HF (human factors) and HCI (human-computer interaction) domains, this book provides integrated design guidance and recommendations for researchers and system developers. It addresses a recognized lack of integration between the HF and HCI research communities, which has led to inconsistencies between the research approaches adopted, and a lack of exploitation of research from one field by the other. The book establishes design guidance through the review of conceptual frameworks, analytical methodologies, and design processes for intelligent adaptive systems.

Arvustused

"This book describes the introduction of automation technologies as a revolution in warfare comparable to the atomic bomb, which is almost certainly true. As such the associated changing role of the human in this revolution in warfare and means and methods by which the human interacts with automation is crucial. The book therefore provides a valuable resource by delivering a comprehensive overview of the current state of thinking as well as the issues and methodologies associated with the development of the human component of increasingly automated and autonomous systems." Ian Ross, BAE Systems

"An excellent guide to the design of intelligent adaptive systems that will be useful to researchers and systems engineers in a variety of work domains. Comprehensive, easy to read, with many figures and illustrations and case studies of incidents and accidents. Should be on the desk on anyone interested in human factors, systems design, and human-automation interaction." Raja Parasuraman, George Mason University, Fairfax, Virginia

" addresses the most important emerging issue in man-machine systems: the teaming of human and machine intelligence to conduct missions in complex environments. does an excellent job of reviewing the pertinent literature in order to develop a basic framework for intelligent adaptive systems." Mr. Michael J Barnes, US Army Research Laboratory

"Quintessential reading for scientists, engineers, practitioners, designers and anyone interested in building and using 21st century human-computer symbiosis technologies. A must read for any serious professional in academia, government or industry. This book documents, illustrates and demonstrates the futuristic vision that J.C. Licklider envisioned in 1960 has arrived." Dylan Schmorrow, Soar Technology, Inc.

"As an operator of military aircraft, I was fascinated right from the start of the first chapter. Having worked with human factors specialists and the designers of robotic support systems in the past, I thought I had a good idea what I would have liked to see in a book about intelligent adaptive systems. But I was amazed how the authors managed to introduce you to real-world examples, present the available academic knowledge, and then lead you through the best practices for the design of intelligent adaptive systems. They never forget that these IAS should not make humans redundant or present a new burden in a complex and extremely challenging environment. I especially liked the idea about the human-machine interaction as a partnership, since this is what the operators of manned and unmanned aircraft need to be able achieve their greatest potential in a wide range of missions and challenges." Roland Runge, German Air Force

List of Figures xv
List of Tables xxiii
Abbreviations xxv
Preface xxvii
Acknowledgments xxix
Authors xxxi
Introduction xxxiii
Chapter 1 Understanding the Human—Machine System
1(30)
1.1 Objectives
1(1)
1.2 Defining Human—Machine System and Intelligent Adaptive System
2(5)
1.2.1 The Human—Machine System
3(2)
1.2.2 The Intelligent Adaptive System
5(2)
1.3 Systems Design and Human—Machine Interaction
7(8)
1.3.1 The Importance of Good Systems Design
7(2)
1.3.2 Determining the Scope of Human—Machine Interaction
9(6)
1.3.2.1 The Pilot Authorisation and Control of Tasks Taxonomy
10(1)
1.3.2.2 Sheridan and Verplank's Levels of Automation Taxonomy
10(2)
1.3.2.3 Endsley and Kaber's Automation Taxonomy
12(1)
1.3.2.4 The Human—Human Interaction Taxonomy
13(2)
1.4 Common Causes of Poor Human—Machine Interaction
15(4)
1.4.1 Technological Issues
16(1)
1.4.2 Human Performance Issues
17(1)
1.4.3 Communication Issues
18(1)
1.5 The Need for Consistent Human—Machine Systems Design Methodologies
19(5)
1.5.1 Domain Differences between Human Factors and Human—Computer Interaction
19(1)
1.5.2 Choosing the Coherence or Correspondence Application Domain
20(4)
1.6 Summary
24(1)
References
24(7)
Section I Theoretical Approaches
Chapter 2 Overview of Intelligent Adaptive Systems
31(36)
2.1 Objectives
31(1)
2.2 The Evolution of Interface Technologies and the IAI Concept
32(11)
2.2.1 Defining Interface
33(1)
2.2.2 Conventional Operator-Machine Interfaces
33(2)
2.2.3 Intelligent Interfaces and Adaptive Interfaces
35(4)
2.2.3.1 Intelligent Interfaces
37(1)
2.2.3.2 Adaptive Interfaces
38(1)
2.2.4 Intelligent Adaptive Interfaces
39(4)
2.2.4.1 IAI Design Considerations
40(2)
2.2.4.2 IAI Design Example
42(1)
2.3 The Evolution of Automation Technologies and the IAA Concept
43(9)
2.3.1 Static Automation
44(1)
2.3.2 Flexible Automation
45(2)
2.3.3 Adaptive Automation
47(2)
2.3.4 Adaptable Automation
49(1)
2.3.5 Intelligent Adaptive Automation
50(1)
2.3.6 Design Basics for IAA
51(1)
2.4 Understanding Intelligent Adaptive Systems
52(8)
2.4.1 The Evolutionary Nature of Intelligent Adaptive Systems
53(1)
2.4.2 IAS Design Objectives
53(2)
2.4.3 Design Basics for IAS
55(2)
2.4.4 Automation and Collaboration
57(3)
2.5 Summary
60(1)
References
61(6)
Chapter 3 Conceptual Architecture for Intelligent Adaptive Systems
67(22)
3.1 Objectives
67(2)
3.2 Existing Conceptual Architectures
69(7)
3.2.1 Early Intelligent Adaptive Systems
69(3)
3.2.1.1 Pilot's Associate Research Program
70(1)
3.2.1.2 Cognitive Cockpit Research Program
71(1)
3.2.2 Other Intelligent Adaptive Systems
72(4)
3.2.2.1 Work-Centered Support System
72(1)
3.2.2.2 Stock Trader System
73(1)
3.2.2.3 Generalized Intelligent Framework for Tutoring
74(1)
3.2.2.4 Edwards' Generic Framework
75(1)
3.3 The Basic Anatomy of Intelligent Adaptive Systems
76(8)
3.3.1 Critical Components of Intelligent Adaptive Systems
76(4)
3.3.1.1 Situation Assessment Module
76(2)
3.3.1.2 Operator State Assessment Module
78(1)
3.3.1.3 Adaptation Engine Module
79(1)
3.3.1.4 Operator—Machine Interface Module
80(1)
3.3.2 How an Intelligent Adaptive System Adapts
80(10)
3.3.2.1 Critical Events
81(1)
3.3.2.2 Operator State and Behavior
82(1)
3.3.2.3 Operator Modeling
82(1)
3.3.2.4 Combination-Based Approach
83(1)
3.4 Summary
84(1)
References
84(5)
Section II Analysis and Design of Intelligent Adaptive Systems
Chapter 4 Analytical Techniques for IAS Design
89(50)
4.1 Objectives
89(1)
4.2 Review of Common Analytical Techniques
90(29)
4.2.1 Mission, Function, and Task Analysis
91(4)
4.2.1.1 Results and Artifacts of MFTA
92(1)
4.2.1.2 Tools and Resources Required
93(1)
4.2.1.3 Strengths and Limitations
93(1)
4.2.1.4 MFTA Applied to a Halifax Class Frigate
94(1)
4.2.2 Hierarchical Task Analysis
95(3)
4.2.2.1 Results and Artifacts of HTA
95(1)
4.2.2.2 Tools and Resources Required
96(1)
4.2.2.3 Strengths and Limitations
97(1)
4.2.2.4 HTA Applied to Medication Management
97(1)
4.2.3 Hierarchical Goal Analysis Based on Perceptual Control Theory
98(2)
4.2.3.1 Results and Artifacts of HGA
98(1)
4.2.3.2 Tools and Resources Required
99(1)
4.2.3.3 Strengths and Limitations
99(1)
4.2.3.4 HGA Applied to a Halifax Class Frigate
99(1)
4.2.4 Goal-Directed Task Analysis
100(1)
4.2.4.1 Results and Artifacts of GDTA
100(1)
4.2.4.2 Tools and Resources Required
101(1)
4.2.4.3 Strengths and Limitations
101(1)
4.2.4.4 GDTA Applied to Army Brigade Officer Teams
101(1)
4.2.5 Cognitive Task Analysis
101(5)
4.2.5.1 Results and Artifacts of CTA
105(1)
4.2.5.2 Tools and Resources Required
105(1)
4.2.5.3 Strengths and Limitations
105(1)
4.2.5.4 CTA Applied to Fireground Commanders
105(1)
4.2.6 Concept Mapping
106(3)
4.2.6.1 Results and Artifacts of Concept Mapping
107(1)
4.2.6.2 Tools and Resources Required
108(1)
4.2.6.3 Strengths and Limitations
108(1)
4.2.6.4 Concept Map of Seasons
109(1)
4.2.7 The Critical Decision Method
109(1)
4.2.7.1 Results and Artifacts of the Critical Decision Method
110(1)
4.2.7.2 Tools and Resources Required
110(1)
4.2.7.3 Strengths and Limitations
110(1)
4.2.8 Team Cognitive Task Analysis
110(2)
4.2.8.1 Results and Artifacts of Team CTA
111(1)
4.2.8.2 Tools and Resources Required
111(1)
4.2.8.3 Strengths and Limitations
111(1)
4.2.9 Cognitive Work Analysis
112(3)
4.2.9.1 Results and Artifacts of CWA
112(1)
4.2.9.2 Tools and Resources Required
113(1)
4.2.9.3 Strengths and Limitations
113(1)
4.2.9.4 CWA Applied to Cardiac Triage
113(2)
4.2.10 Comparing Analytical Techniques
115(4)
4.3 Review of Common Design Techniques
119(7)
4.3.1 Participatory Design
119(1)
4.3.2 United States Department of Defense Architecture Framework
120(3)
4.3.2.1 Tools and Resources Required
123(1)
4.3.2.2 Strengths and Limitations
123(1)
4.3.3 Ecological Interface Design
123(3)
4.3.3.1 Tools and Resources Required
124(1)
4.3.3.2 Strengths and Limitations
124(1)
4.3.3.3 EID Applied to Cardiac Triage
124(2)
4.3.4 Comparing Design Techniques
126(1)
4.4 Creating a Hybrid Technique
126(8)
4.4.1 Identifying Project Requirements and Constraints
126(1)
4.4.2 Selecting Analytical Techniques
127(3)
4.4.3 Using a MFTA/GDTA/CTA Hybrid Analytical Technique
130(4)
4.4.3.1 Step 1: Mission and Function Analysis
130(1)
4.4.3.2 Step 2: Goal, Decision, and Situation Awareness Requirements Analysis
130(1)
4.4.3.3 Step 3: Cognitive Risk Analysis
130(4)
4.4.4 Understanding the Overall Analysis
134(1)
4.5 Summary
134(1)
References
135(4)
Chapter 5 Agent-Based, Interaction-Centered IAS Design
139(42)
5.1 Objectives
139(1)
5.2 Defining Agents in the Context of IAS Design
140(5)
5.2.1 Corporate Interaction as an Analogy of Operator—Agent Interaction
140(2)
5.2.2 Agents
142(1)
5.2.3 Agent Intelligence
142(2)
5.2.4 Agent Adaptivity
144(1)
5.3 Benefiting from Agent-Based Approaches in IAS Design
145(3)
5.3.1 Common Interface Design Methods
146(1)
5.3.2 Advantages of an Agent-Based Approach
147(1)
5.4 Designing Agents
148(17)
5.4.1 Agent-Based Design Methods
150(11)
5.4.1.1 Common Knowledge Acquisition and Documentation Structuring
150(2)
5.4.1.2 Integrated Computer-Aided Manufacturing Definition
152(1)
5.4.1.3 Explicit Models Design
153(2)
5.4.1.4 Ecological Interface Design
155(1)
5.4.1.5 Belief-Desire-Intention
156(3)
5.4.1.6 Blackboard
159(2)
5.4.2 Interaction-Centered Design
161(4)
5.4.3 Operator—Agent Interaction
165(1)
5.5 Agent-Based, Interaction-Centered IAS Design Framework
165(8)
5.5.1 Managing Agent
166(1)
5.5.2 Senior Agents
167(1)
5.5.3 Working Agents
168(1)
5.5.4 Function Allocation and Adaptation Processes
169(2)
5.5.5 Agent Interaction
171(2)
5.6 Summary
173(1)
References
174(7)
Chapter 6 Operator State Monitoring Approaches
181(36)
6.1 Objectives
181(1)
6.2 Using Operator State Monitoring Approaches
182(3)
6.3 Behavioral-Based Monitoring
185(2)
6.3.1 Operator—Control Interaction Monitoring
186(1)
6.3.2 Voice Recognition and Auditory Analysis
186(1)
6.4 Psychophysiological-Based Monitoring
187(14)
6.4.1 Electroencephalogram
190(1)
6.4.2 Near-Infrared Spectroscopy
191(1)
6.4.3 Electrodermal Response
192(2)
6.4.4 Cardiovascular Measurements
194(1)
6.4.4.1 Electrocardiogram
194(1)
6.4.4.2 Heart Rate and Heart Rate Variability
194(1)
6.4.5 Eye Tracking
195(2)
6.4.6 Respiration Measurements
197(1)
6.4.7 Skin Temperature Measurements
198(1)
6.4.8 Electromyography
198(1)
6.4.9 Choosing Psychophysiological Monitoring Approaches
199(2)
6.5 Contextual-Based Monitoring
201(3)
6.5.1 Ambient Sensors
203(1)
6.5.2 System State Sensors
203(1)
6.6 Subjective-Based Monitoring
204(1)
6.7 Combination-Based Monitoring
204(3)
6.7.1 Rule-Based Data Fusion
205(1)
6.7.2 Artificial Neural Networks
205(2)
6.8 An Example Combination-Based Monitoring System
207(2)
6.9 Summary
209(1)
References
210(7)
Chapter 7 Key Considerations for IAS Design
217(24)
7.1 Objectives
217(1)
7.2 Considering Design Constraints
218(1)
7.3 Determining Operational Priorities
219(2)
7.4 Considering Ethical, Legal, Social, and Cultural Issues
221(2)
7.5 Determining Authority Roles
223(2)
7.6 Determining Range of Adaptation
225(2)
7.6.1 Modification of Function Allocation
225(1)
7.6.2 Modification of Task Scheduling
226(1)
7.6.3 Modification of Interaction
227(1)
7.6.4 Modification of Content
227(1)
7.7 Determining Adaptation Triggers
227(4)
7.7.1 Operator-Based Triggers
228(1)
7.7.2 Machine-Based Triggers
228(1)
7.7.3 Environment-Based Triggers
228(1)
7.7.4 Mission- and Task-Based Triggers
229(1)
7.7.5 Location- and Time-Based Triggers
229(1)
7.7.6 Selecting Adaptation Triggers
230(1)
7.8 Developing an Adaptation Taxonomy
231(5)
7.9 Summary
236(1)
References
236(5)
Section III Practical Applications
Chapter 8 Case Studies
241(46)
8.1 Objectives
241(1)
8.2 Designing an Uninhabited Aerial Vehicle Operator-Machine Interface
241(25)
8.2.1 The Importance of IAI for UAV Control
242(1)
8.2.2 IAI Project Scope
242(1)
8.2.3 IAI Design and Development Road Map
243(16)
8.2.3.1 Determining Operational Priorities
244(2)
8.2.3.2 Ethical and Legal Implications
246(1)
8.2.3.3 Selecting an Analytical Technique
246(2)
8.2.3.4 Determining Range of Adaptation
248(6)
8.2.3.5 Selecting Adaptation Triggers
254(3)
8.2.3.6 Testing Design Concepts
257(2)
8.2.4 IAI Implementation
259(2)
8.2.5 IAI Evaluation
261(5)
8.3 Designing an Intelligent Tutoring System
266(17)
8.3.1 The Importance of Questioning Technique for IEDD Identification
267(1)
8.3.2 IEDD Operator Course
268(1)
8.3.3 QuestionIT Design and Development Road Map
269(12)
8.3.3.1 Determining Operational Priorities
269(1)
8.3.3.2 Ethical and Legal Implications
270(1)
8.3.3.3 Selecting an Analytical Technique
271(2)
8.3.3.4 Determining Range of Adaptation
273(5)
8.3.3.5 Selecting the Operator Monitoring Approach
278(3)
8.3.4 QuestionIT Implementation
281(1)
8.3.5 QuestionIT Evaluation
282(1)
8.4 Summary
283(1)
References
284(3)
Subject Index 287(6)
Author Index 293
Dr. Ming Hou is a senior defence scientist at Defence Research and Development Canada (DRDC) Toronto, where he is responsible for providing science-based advice to the Canadian Armed Forces about the investment in and application of advanced technologies for human-machine systems requirements. His research interests include applied cognition, intelligent adaptive interface and systems design, human-technology/automation interaction, intelligent tutoring, and stereoscopic virtual and mixed reality displays. Dr. Hou is the Canadian National Leader of the Human Systems Performance Technical Panel for the Air in The Technical Cooperation Program (TTCP). He also serves several NATO working groups. Dr. Hou is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Human Factors and Ergonomics Society, and a member of the Association of Computing Machinery.

Dr. Simon Banbury is the owner and president of Looking Glass HF Inc., an independent Canadian-based human factors consultancy specializing in optimizing how people interact with technology. He is also a Professeur Associé of the School of Psychology at Université Laval (Canada) where he supervises PhD students and supports teamwork and medical decision making research. Dr. Banbury has almost twenty years of human factors consultancy and applied research experience in defence, industrial, and academic domains; he has worked as a human factors consultant in the defence and industrial sectors, as a lecturer of psychology at Cardiff University, and as a defence scientist for the United Kingdoms Defence Evaluation and Research Agency (DERA).

Dr. Catherine Burns is a systems design engineering professor and the founding director of the Centre for Bioengineering and Biotechnology at the University of Waterloo (Canada). At Waterloo she also directs the Advanced Interface Design Lab. Her research examines user interface design, visualization, and cognitive work analysis and her work has been applied in military, healthcare, power plant control, and oil and gas refining domains. She regularly consults with companies in the areas of human performance in complex systems, interface design, and traditional human factors engineering. Dr. Burns has authored over 200 publications, co-authored a book on ecological interface design, and co-edited Applications of Cognitive Work Analysis. She has been the program chair for the Cognitive Engineering and Decision Making Technical Group of the Human Factors and Ergonomics Society and has been awarded both teaching and research excellence awards at the University of Waterloo.
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