Explainable and Transparent AI and Multi-Agent Systems

4th International Workshop, EXTRAAMAS 2022, Virtual Event, May 9-10, 2022, Revised Selected Papers
1. Auflage 2022
ISBN: 978-3-031-15564-2
Verlag: Springer

Buch, Englisch, 239 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 388 g

Reihe: Lecture Notes in Artificial Intelligence

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. 

Zielgruppe

Research

Autoren/Hrsg.

Calvaresi, Davide

Najjar, Amro

Winikoff, Michael

Främling, Kary

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

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.