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Explainable and Transparent AI and Multi-Agent Systems

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Cover of 'Explainable and Transparent AI and Multi-Agent Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Evaluation of Importance Estimators in Deep Learning Classifiers for Computed Tomography
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    Chapter 2 Integration of Local and Global Features Explanation with Global Rules Extraction and Generation Tools
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    Chapter 3 ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning
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    Chapter 4 Smartphone Based Grape Leaf Disease Diagnosis and Remedial System Assisted with Explanations
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    Chapter 5 Recent Neural-Symbolic Approaches to ILP Based on Templates
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    Chapter 6 On the Design of PSyKI: A Platform for Symbolic Knowledge Injection into Sub-symbolic Predictors
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    Chapter 7 The Mirror Agent Model: A Bayesian Architecture for Interpretable Agent Behavior
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    Chapter 8 Semantic Web-Based Interoperability for Intelligent Agents with PSyKE
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    Chapter 9 Case-Based Reasoning via Comparing the Strength Order of Features
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    Chapter 10 Explainability Metrics and Properties for Counterfactual Explanation Methods
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    Chapter 11 The Use of Partial Order Relations and Measure Theory in Developing Objective Measures of Explainability
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    Chapter 12 An Evaluation of Methodologies for Legal Formalization
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    Chapter 13 Risk and Exposure of XAI in Persuasion and Argumentation: The case of Manipulation
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    Chapter 14 Requirements for Tax XAI Under Constitutional Principles and Human Rights
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Title
Explainable and Transparent AI and Multi-Agent Systems
Published by
Springer International Publishing, September 2022
DOI 10.1007/978-3-031-15565-9
ISBNs
978-3-03-115564-2, 978-3-03-115565-9
Editors

Calvaresi, Davide, Najjar, Amro, Winikoff, Michael, Främling, Kary

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