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Cover: 9783031408779 | Explainable and Transparent AI and Multi-Agent Systems | Taschenbuch
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Explainable and Transparent AI and Multi-Agent Systems
5th International Workshop, EXTRAAMAS 2023, London, UK, May 29, 2023, Revised Selected Papers
Taschenbuch von Davide Calvaresi (u. a.)
Sprache: Englisch

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Beschreibung
This volume LNCS 14127 constitutes the refereed proceedings of the 5th International Workshop, EXTRAAMAS 2023, held in London, UK, in May 2023.
The 15 full papers presented together with 1 short paper were carefully reviewed and selected from 26 submissions. The workshop focuses on Explainable Agents and multi-agent systems; Explainable Machine Learning; and Cross-domain applied XAI.
This volume LNCS 14127 constitutes the refereed proceedings of the 5th International Workshop, EXTRAAMAS 2023, held in London, UK, in May 2023.
The 15 full papers presented together with 1 short paper were carefully reviewed and selected from 26 submissions. The workshop focuses on Explainable Agents and multi-agent systems; Explainable Machine Learning; and Cross-domain applied XAI.
Inhaltsverzeichnis
¿Explainable Agents and multi-agent systems.- Mining and Validating Belief-based Agent Explanations.- Evaluating a mechanism for explaining BDI agent behaviour.- A General-Purpose Protocol for Multi-Agent based Explanations.- Dialogue Explanations for Rules-based AI Systems.- Estimating Causal Responsibility for Explaining Autonomous Behavior.- Explainable Machine Learning.- The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing.- Bottom-Up and Top-Down Workflows for Hypercube- and Clustering-based Knowledge Extractors.- Imperative Action Masking for Safe Exploration in Reinforcement Learning.- Reinforcement Learning in Cyclic Environmental Change for Non-Communicative Agents: A Theoretical Approach.- Inherently Interpretable Deep Reinforcement Learning through Online Mimicking.- Counterfactual, Contrastive, and Hierarchical Explanations with Contextual Importance and Utility.- Cross-domain applied XAI.- Explanation Generation via Decompositional Rules Extraction for Head and Neck Cancer Classification.- Metrics for Evaluating Explainable Recommender Systems.- Leveraging Imperfect Explanations for Plan Recognition Problems.- Reinterpreting Vulnerability to Tackle Deception in Principles-Based XAI for Human-Computer Interaction.- Using Cognitive Models and Wearables to Diagnose and Predict Dementia Patient Behaviour.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 296
Reihe: Lecture Notes in Artificial Intelligence
Inhalt: xii
281 S.
22 s/w Illustr.
47 farbige Illustr.
281 p. 69 illus.
47 illus. in color.
ISBN-13: 9783031408779
ISBN-10: 3031408772
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Redaktion: Calvaresi, Davide
Najjar, Amro
Omicini, Andrea
Främling, Kary
Carli, Rachele
Ciatto, Giovanni
Mualla, Yazan
Aydogan, Reyhan
Herausgeber: Davide Calvaresi/Amro Najjar/Andrea Omicini et al
Auflage: 1st ed. 2023
Hersteller: Springer Nature Switzerland
Springer International Publishing
Lecture Notes in Artificial Intelligence
Maße: 235 x 155 x 17 mm
Von/Mit: Davide Calvaresi (u. a.)
Erscheinungsdatum: 05.09.2023
Gewicht: 0,452 kg
preigu-id: 127243525
Inhaltsverzeichnis
¿Explainable Agents and multi-agent systems.- Mining and Validating Belief-based Agent Explanations.- Evaluating a mechanism for explaining BDI agent behaviour.- A General-Purpose Protocol for Multi-Agent based Explanations.- Dialogue Explanations for Rules-based AI Systems.- Estimating Causal Responsibility for Explaining Autonomous Behavior.- Explainable Machine Learning.- The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing.- Bottom-Up and Top-Down Workflows for Hypercube- and Clustering-based Knowledge Extractors.- Imperative Action Masking for Safe Exploration in Reinforcement Learning.- Reinforcement Learning in Cyclic Environmental Change for Non-Communicative Agents: A Theoretical Approach.- Inherently Interpretable Deep Reinforcement Learning through Online Mimicking.- Counterfactual, Contrastive, and Hierarchical Explanations with Contextual Importance and Utility.- Cross-domain applied XAI.- Explanation Generation via Decompositional Rules Extraction for Head and Neck Cancer Classification.- Metrics for Evaluating Explainable Recommender Systems.- Leveraging Imperfect Explanations for Plan Recognition Problems.- Reinterpreting Vulnerability to Tackle Deception in Principles-Based XAI for Human-Computer Interaction.- Using Cognitive Models and Wearables to Diagnose and Predict Dementia Patient Behaviour.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 296
Reihe: Lecture Notes in Artificial Intelligence
Inhalt: xii
281 S.
22 s/w Illustr.
47 farbige Illustr.
281 p. 69 illus.
47 illus. in color.
ISBN-13: 9783031408779
ISBN-10: 3031408772
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Redaktion: Calvaresi, Davide
Najjar, Amro
Omicini, Andrea
Främling, Kary
Carli, Rachele
Ciatto, Giovanni
Mualla, Yazan
Aydogan, Reyhan
Herausgeber: Davide Calvaresi/Amro Najjar/Andrea Omicini et al
Auflage: 1st ed. 2023
Hersteller: Springer Nature Switzerland
Springer International Publishing
Lecture Notes in Artificial Intelligence
Maße: 235 x 155 x 17 mm
Von/Mit: Davide Calvaresi (u. a.)
Erscheinungsdatum: 05.09.2023
Gewicht: 0,452 kg
preigu-id: 127243525
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