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Titlebook: Explainable and Transparent AI and Multi-Agent Systems; 5th International Wo Davide Calvaresi,Amro Najjar,Kary Fr?mling Conference proceedi

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發(fā)表于 2025-3-21 20:07:50 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Explainable and Transparent AI and Multi-Agent Systems
副標(biāo)題5th International Wo
編輯Davide Calvaresi,Amro Najjar,Kary Fr?mling
視頻videohttp://file.papertrans.cn/320/319307/319307.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Explainable and Transparent AI and Multi-Agent Systems; 5th International Wo Davide Calvaresi,Amro Najjar,Kary Fr?mling Conference proceedi
描述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...?..
出版日期Conference proceedings 2023
關(guān)鍵詞Multiagent Systems; Machine Learning; Compilers and Interpreters; Natural Language Processing (NLP); The
版次1
doihttps://doi.org/10.1007/978-3-031-40878-6
isbn_softcover978-3-031-40877-9
isbn_ebook978-3-031-40878-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 22:07:40 | 只看該作者
Handbook of Youth Suicide Preventionstem predictability. Previous work has proposed an explanation mechanism for Belief-Desire-Intention (BDI) agents that uses folk psychological concepts, specifically beliefs, desires, and valuings. In this paper we evaluate this mechanism by conducting a survey. We consider a number of explanations,
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發(fā)表于 2025-3-22 01:56:32 | 只看該作者
The Victimization of Children and Youth agents may need to provide explanations for their recommendations. The protocol specifies the roles and responsibilities of the explainee and the explainer agent and the types of information that should be exchanged between them to ensure a clear and effective explanation. However, it does not pres
地板
發(fā)表于 2025-3-22 06:18:22 | 只看該作者
Takashi Ogawa,Akihiko Masuda,Kayla Sargentn harm and, in the worst cases, death. Explainable Artificial Intelligence (XAI) tries to produce human-understandable explanations for AI decisions. However, most XAI systems prioritize factors such as technical complexities and research-oriented goals over end-user needs, risking information overl
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發(fā)表于 2025-3-22 10:33:39 | 只看該作者
S. De Spirt,W. Stahl,U. Heinrichg offer several theoretical benefits when exact inference can be applied. Furthermore, users overwhelmingly prefer the resulting causal explanations over other state-of-the-art systems. In this work, we focus on one such method, ., and its approximate versions that drastically reduce compute load an
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發(fā)表于 2025-3-22 16:14:29 | 只看該作者
Handbook of nutrition, diet and sleepenarios. This is the main reason behind many approaches focusing on local post-hoc explanations recently proposed by the XAI community. However, to the best of our knowledge, a thorough comparison among available explainability techniques is currently missing, mainly for the lack of a general metric
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Handbook of the Brief Psychotherapiesety hazards, not necessarily in the next state but in the future. Therefore, it is essential to evaluate each action beforehand to ensure safety. The exploratory actions and the actions proposed by the RL agent could also be unsafe during training and in the deployment phase. In this work, we have p
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