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Explainable and Transparent AI and Multi-Agent Systems de Davide Calvaresi

Explainable and Transparent AI and Multi-Agent Systems: Lecture Notes in Computer Science, cartea 13283

Editat de Davide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling
en Limba Engleză Paperback – 23 sep 2022
This book constitutes the refereed proceedings of the 4th International Workshop on Explainable and Transparent AI and Multi-Agent Systems, EXTRAAMAS 2022, held virtually during May 9–10, 2022. 

The 14 full papers included in this book were carefully reviewed and selected from 25 submissions. They were organized in topical sections as follows: explainable machine learning; explainable neuro-symbolic AI; explainable agents; XAI measures and metrics; and AI & law. 

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Specificații

ISBN-13: 9783031155642
ISBN-10: 3031155645
Pagini: 252
Ilustrații: IX, 239 p. 38 illus., 31 illus. in color.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.39 kg
Ediția:1st edition 2022
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

​Explainable Machine Learning.- Evaluation of importance estimators in deep learning classifiers for Computed Tomography.- Integration of local and global features explanation with global rules extraction and generation tools.- ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning.- Smartphone based grape leaf disease diagnosis and remedial system Assisted with explanations.- Explainable Neuro-Symbolic AI.- Recent Neural-Symbolic Approaches to ILP Based on Templates.- On the Design of PSyKI: a Platform for Symbolic Knowledge Injection into Sub-Symbolic Predictors.- Explainable Agents.- The Mirror Agent Model: a Bayesian Architecture for Interpretable Agent Behavior.- Semantic Web-based Interoperability for Intelligent Agents with PsyKE.- Case-based reasoning via comparing the strength order of features.- XAI Measures and Metrics.- Explainability Metrics and Properties for Counterfactual Explanation Methods.- The use of partial order relations and measure theory in developing objective measures of explainability.- AI & Law.- An Evaluation of Methodologies for Legal Formalization.- Risk and Exposure of XAI in Persuasion and Argumentation: The case of Manipulation.- Requirements for Tax XAI under Constitutional Principles and Human Rights.