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Explainable, Trustworthy, and Responsible AI and Multi-Agent Systems: 7th International Workshop, EXTRAAMAS 2025, Detroit, MI, USA, May 1920, 2025, Revised Selected Papers [Pehme köide]

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  • Formaat: Paperback / softback, 244 pages, kõrgus x laius: 235x155 mm, 40 Illustrations, color; 11 Illustrations, black and white
  • Sari: Lecture Notes in Computer Science
  • Ilmumisaeg: 10-Oct-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032013984
  • ISBN-13: 9783032013989
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Explainable, Trustworthy, and Responsible AI and Multi-Agent Systems: 7th International Workshop, EXTRAAMAS 2025, Detroit, MI, USA, May 1920, 2025, Revised Selected PapersSuurem pilt
  • Formaat: Paperback / softback, 244 pages, kõrgus x laius: 235x155 mm, 40 Illustrations, color; 11 Illustrations, black and white
  • Sari: Lecture Notes in Computer Science
  • Ilmumisaeg: 10-Oct-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032013984
  • ISBN-13: 9783032013989
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783032013989.html
Märksõnad:
This book constitutes the refereed post-conference proceedings of the 7th International Workshop on Explainable and Transparent AI and Multi-Agent Systems, EXTRAAMAS 2025, held in Detroit, MI, USA, during May 19-20, 2025.



The 12 full papers and 1 short paper included in this book were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: AI interpretation & social dimensions; LLMs & generative AI in XAI; agent architectures & inter-agent explainability; and human-XAI interaction, quality & ethics.
AI Interpretation & Social Dimensions.- Enhancing Surrogate Decision
Trees for Reinforcement Learning with Feature Importance Matrices.-
Exploiting Constraint Reasoning to Build Graphical Explanations for
Mixed-Integer Linear Programming.- Explaining Autonomous Vehicles with
Intention-aware Policy Graphs.- Social Explainable AI: What Is It and How to
Make It Happen with CIU?- LLMs & Generative AI in XAI.- Evaluating Prompt
Engineering Techniques for Accuracy and Confidence Elicitation in Medical
LLMs.- LLM-based Evaluation Methodology of Explanation Strategies.- LLM-based
Evaluation Methodology of Explanation Strategies.- Agent Architectures &
Inter-Agent Explainability.- Ladder of Intentions: Unifying Agent
Architectures for Explainability and Transferability.- Engineering
Inter-Agent Explainability in BDI Agents.- Human-XAI Interaction, Quality &
Ethics.- Beyond Satisfaction: From Placebic to Actionable Explanations For
Enhanced Understandability.- Building a Decolonized AI Ethics and Governance
Framework.- Balancing Ethical Persuasion and Explanation Transparency in
XAI.- Designing for Effective Human-XAI Inter-action.