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Titlebook: Human-Centered Artificial Intelligence; Advanced Lectures Mohamed Chetouani,Virginia Dignum,Carles Sierra Textbook 2023 Springer Nature Swi

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發(fā)表于 2025-3-23 11:09:14 | 只看該作者
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發(fā)表于 2025-3-23 17:05:40 | 只看該作者
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發(fā)表于 2025-3-23 19:38:45 | 只看該作者
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發(fā)表于 2025-3-24 01:19:43 | 只看該作者
Artificial Visual Intelligenceents general methods for the processing and semantic interpretation of dynamic visuospatial imagery with a particular emphasis on the ability to abstract, learn, and reason with cognitively rooted structured characterisations of commonsense knowledge pertaining to space and motion. The presented wor
15#
發(fā)表于 2025-3-24 06:14:09 | 只看該作者
An Introduction to Ethics and AIcus on the fact that not all problems can be solved by technological advancements. Second, we introduce what is Ethics and how AI may need changing it. Finally, we will consider how AI can impact current ethical theories.
16#
發(fā)表于 2025-3-24 08:51:27 | 只看該作者
Law for Computer Scientistsh computer science or AI. In the second part we will zoom in on a set of texts that are highly relevant for computer science and AI. A first aspect we discuss the content of legal norms that apply to the processing of personal data, followed by a brief analysis of the proposed AI Act.
17#
發(fā)表于 2025-3-24 11:04:55 | 只看該作者
18#
發(fā)表于 2025-3-24 17:52:52 | 只看該作者
Artificial Visual Intelligencek constitutes a systematic model and methodology integrating diverse, multi-faceted AI methods pertaining Knowledge Representation and Reasoning, Computer Vision, and Machine Learning towards realising practical, human-centred artificial visual intelligence.
19#
發(fā)表于 2025-3-24 19:24:04 | 只看該作者
Textbook 2023ntains 21 tutorial chapters organized according to the following themes: human-centered AI; human-centered machine learning; explainable AI; ethics, law, and the societal aspects of AI; argumentation; and social simulation. The contributions include learning objectives, reading lists, and links to further resources..
20#
發(fā)表于 2025-3-24 23:23:00 | 只看該作者
Interactive Robot Learning: An Overviewching. We then present applications such as interactive task learning, robot behavior learning and socially assistive robotics. Finally, we discuss research opportunities and challenges of interactive robot learning.
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