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Titlebook: Janusz Czelakowski on Logical Consequence; Jacek Malinowski,Rafa? Palczewski Book 2024 The Editor(s) (if applicable) and The Author(s), un

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樓主: radionuclides
31#
發(fā)表于 2025-3-26 23:30:16 | 只看該作者
in the other. Changes in our understanding of how the human mind works inadvertently changes how we go about creating artificial minds. Similarly, successes and failures in AI can inspire new directions to be taken in cognitive science. This article explores the history of the mind in cognitive scie
32#
發(fā)表于 2025-3-27 03:55:47 | 只看該作者
Jacek Malinowski,Rafa? Palczewskixplanation directly from an intelligent agent. We propose Conversational Interfaces (CIs) to be the perfect setting, since they are intuitive for humans and computationally processible. While there are many approaches addressing technical and agent related issues of this human-agent communication pr
33#
發(fā)表于 2025-3-27 08:26:12 | 只看該作者
34#
發(fā)表于 2025-3-27 12:30:01 | 只看該作者
35#
發(fā)表于 2025-3-27 15:29:43 | 只看該作者
Jacek Malinowskihere are still few experimental studies on how transparency affects teamwork, in particular in collaborative situations where the strategies of others, including agents, may seem obscure..We explored this problem using a collaborative game scenario with a mixed human-agent team. We investigated the
36#
發(fā)表于 2025-3-27 21:22:53 | 只看該作者
gents often use Machine Learning (ML) for acquiring expertise, but traditional ML methods produce opaque results which are difficult to interpret. Hence, these autonomous agents should be able to explain their behaviour and decisions before they can be trusted by humans. This paper focuses on analyz
37#
發(fā)表于 2025-3-28 00:16:00 | 只看該作者
Josep Maria Font,Ramon Jansanad by humans. On the one hand, systems dealing with strict-timing constraints in safety-critical applications mainly focused on predictability, leaving little room for complex planning and decision-making processes. Indeed, real-time techniques are very efficient in predetermined, constrained, and co
38#
發(fā)表于 2025-3-28 02:30:36 | 只看該作者
Tommaso Moraschinigents often use Machine Learning (ML) for acquiring expertise, but traditional ML methods produce opaque results which are difficult to interpret. Hence, these autonomous agents should be able to explain their behaviour and decisions before they can be trusted by humans. This paper focuses on analyz
39#
發(fā)表于 2025-3-28 07:19:02 | 只看該作者
Miguel Campercholi,Diego Casta?ogents often use Machine Learning (ML) for acquiring expertise, but traditional ML methods produce opaque results which are difficult to interpret. Hence, these autonomous agents should be able to explain their behaviour and decisions before they can be trusted by humans. This paper focuses on analyz
40#
發(fā)表于 2025-3-28 11:04:37 | 只看該作者
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