Modeling and Use of Context in Action

Herausgegeben:Brézillon, Patrick; Turner, Roy M.

• Gebundenes Buch

Produktbeschreibung

This book brings together current research and adopts a pragmatic approach to modeling and using context to solve real-world problems. The editors were instrumental in creating - and continue to be involved in - the interdisciplinary research community, centered around the biennial CONTEXT (International and Interdisciplinary Conference on Modeling and Using Context) conference series, focused on studying context and its implications for artificial intelligence, software applications, psychology, philosophy, linguistics, neuroscience, as well as other fields.

The first three chapters lay the foundations, looking at the lessons learned over the past 25 years and arguing for a continued shift toward more pragmatic approaches. The remaining chapters contain contributions to pragmatic context-based research from a wide range of domains, including technological problems - such as subway incident management and autonomous underwater vehicle control - identifying emotions from speech without understanding the words, anonymization in a world where privacy is increasingly threatened, teaching in context and improving management teaching in a business school.

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Produktdetails

• Verlag: Wiley & Sons / Wiley-ISTE
• Artikelnr. des Verlages: 1W786308290
• 1. Auflage
• Seitenzahl: 320
• Erscheinungstermin: 21. September 2022
• Englisch
• Abmessung: 240mm x 161mm x 21mm
• Gewicht: 666g
• ISBN-13: 9781786308290
• ISBN-10: 1786308290
• Artikelnr.: 64541620

Autorenporträt

Patrick Brezillon is Professor Emeritus at Sorbonne University, France. His research focuses on context modeling and its use in applications and has culminated in the Contextual-Graph software. This research focus is shared by a large community that has been active for almost 25 years. Roy M. Turner is Associate Professor of computer science at the University of Maine, USA. His research area is artificial intelligence, focusing in particular on context-sensitive reasoning, deep learning in context, intelligent real-world agent control and computational ecology.

Inhaltsangabe

Preface xi

Patrick Brézillon and Roy M. Turner

Introduction xxi

Patrick Brézillon and Roy M. Turner

Chapter 1 Pragmatic Research on Context Modeling and Use 1

Patrick Brézillon and Roy M. Turner

1.1 Introduction 1

1.2 Pragmatic research on context 2

1.3 Role of context in AI systems 3

1.3.1 Data, information and knowledge 3

1.3.2 Contextual knowledge 6

1.4 Three examples of pragmatic research on context 8

1.4.1 Introduction 8

1.4.2 Contextual graphs (CxGs) 9

1.4.3 Context-based reasoning (CxBR) 11

1.4.4 Context-mediated behavior (CMB) 12

1.4.5 Conclusions and lessons learned 14

1.5 Conclusion 18

1.6 References 19

Chapter 2. Modeling and Using Context: 25 Years of Lessons Learned 23

Patrick Brézillon

2.1 Introduction 23

2.2 Knowledge in action 25

2.2.1 Operational knowledge and contextual knowledge 25

2.2.2 Operational knowledge and mental models 26

2.2.3 Modeling operational knowledge 27

2.2.4 Indirect modeling from experience reuse 29

2.2.5 Lessons learned 31

2.3 Context in action 32

2.3.1 Conceptual modeling 32

2.3.2 A typology of contexts 33

2.3.3 About contextual elements 34

2.3.4 Implementation of the contextual graphs formalism 39

2.4 Using context in real-world applications 40

2.4.1 Context and focus processing 40

2.4.2 Context and actors 42

2.4.3 Extension of the CxG formalism 43

2.5 Conclusion 46

2.6 References 49

Chapter 3 Toward Pragmatic Context-Based Intelligent Systems 53

Roy M. Turner and Patrick Brézillon

3.1 Introduction 53

3.2 Evolution of AI systems 55

3.2.1 Formal versus pragmatic acontextual approaches 55

3.2.2 Formal consideration of context 56

3.2.3 Pragmatic consideration of context 57

3.3 Pragmatic context-based intelligent systems 62

3.3.1 Explicit context representation 63

3.3.2 Context assessment mechanism 66

3.3.3 Context transitioning mechanism 68

3.3.4 Context-based intelligent assistant systems 68

3.3.5 Context-based intelligent autonomous agents 73

3.4 Conclusion 80

3.5 References 81

Chapter 4 Activating the Context for Learning and Teaching: Findings from the TEEC Project 87

Claire Anjou, Thomas Forissier, Jacqueline Bourdeau, Valéry Psyché, Lamprini Chartofylaka and Alain Stockless

4.1 Introduction 87

4.2 Theoretical framework 89

4.2.1 Internal and external contexts for education 89

4.2.2 Modeling external context 91

4.3 The research focuses 95

4.4 Methodology 98

4.4.1 DBR methodology 98

4.4.2 Data collection and analysis 99

4.4.3 TEEC organization 99

4.5 Results and findings 101

4.5.1 Context effects identification and specification 101

4.5.2 Using the digital technologies 105

4.5.3 Learning as an evolution of mental representations 106

4.5.4 The development of digital tools 107

4.6 Discussion and interpretation 114

4.6.1 Context effect and affective dimension: learning with contexts, contexts effect and cognitive conflict 114

4.6.2 Digital education and context 117

4.6.3 Mazcalc needs to interact with the scripting tool 118

4.7 Conclusion and related work 118

4.8 Acknowledgment and credits 120

4.9 Appendices: description