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Robust Intelligence and Trust in Autonomous Systems

Overview of attention for book
Cover of 'Robust Intelligence and Trust in Autonomous Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Towards Modeling the Behavior of Autonomous Systems and Humans for Trusted Operations
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    Chapter 3 Learning Trustworthy Behaviors Using an Inverse Trust Metric
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    Chapter 4 The “Trust V”: Building and Measuring Trust in Autonomous Systems
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    Chapter 5 Big Data Analytic Paradigms: From Principle Component Analysis to Deep Learning
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    Chapter 6 Artificial Brain Systems Based on Neural Network Discrete Chaotic Dynamics. Toward the Development of Conscious and Rational Robots
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    Chapter 7 Modeling and Control of Trust in Human-Robot Collaborative Manufacturing
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    Chapter 8 Investigating Human-Robot Trust in Emergency Scenarios: Methodological Lessons Learned
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    Chapter 9 Designing for Robust and Effective Teamwork in Human-Agent Teams
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    Chapter 10 Measuring Trust in Human Robot Interactions: Development of the “ Trust Perception Scale-HRI ”
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    Chapter 11 Methods for Developing Trust Models for Intelligent Systems
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    Chapter 12 The Intersection of Robust Intelligence and Trust: Hybrid Teams, Firms and Systems
Attention for Chapter 9: Designing for Robust and Effective Teamwork in Human-Agent Teams
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Readers on

mendeley
31 Mendeley
Summary
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Chapter title
Designing for Robust and Effective Teamwork in Human-Agent Teams
Chapter number 9
Book title
Robust Intelligence and Trust in Autonomous Systems
Published by
Springer, Boston, MA, January 2016
DOI 10.1007/978-1-4899-7668-0_9
Book ISBNs
978-1-4899-7666-6, 978-1-4899-7668-0
Authors

Fei Gao, M. L. Cummings, Erin Solovey, Gao, Fei, Cummings, M. L., Solovey, Erin

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 29%
Student > Master 5 16%
Student > Doctoral Student 4 13%
Researcher 4 13%
Professor 3 10%
Other 5 16%
Unknown 1 3%
Readers by discipline Count As %
Engineering 9 29%
Computer Science 7 23%
Psychology 5 16%
Design 3 10%
Decision Sciences 2 6%
Other 4 13%
Unknown 1 3%

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