Explainable and Transparent AI and Multi-Agent Systems〈1st ed. 2023〉 : 5th International Workshop, EXTRAAMAS 2023, London, UK, May 29, 2023, Revised Selected Papers

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Explainable and Transparent AI and Multi-Agent Systems〈1st ed. 2023〉 : 5th International Workshop, EXTRAAMAS 2023, London, UK, May 29, 2023, Revised Selected Papers

  • 言語:ENG
  • ISBN:9783031408779
  • eISBN:9783031408786

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Description

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.

 


Table of Contents

​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.

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