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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 1st ed. 2023 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 281 pages, height x width: 235x155 mm, weight: 456 g, 47 Illustrations, color; 22 Illustrations, black and white; XII, 281 p. 69 illus., 47 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 14127
  • Izdošanas datums: 05-Sep-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031408772
  • ISBN-13: 9783031408779
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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 1st ed. 2023Palielināt
  • Formāts: Paperback / softback, 281 pages, height x width: 235x155 mm, weight: 456 g, 47 Illustrations, color; 22 Illustrations, black and white; XII, 281 p. 69 illus., 47 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 14127
  • Izdošanas datums: 05-Sep-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031408772
  • ISBN-13: 9783031408779
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031408779.html
Keywords:
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.





 
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.