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Titlebook: Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal,Contextual and Causal Inference; Ben Goertzel,Nil Geisweiller,Cassio Penna

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發(fā)表于 2025-3-30 09:53:16 | 只看該作者
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發(fā)表于 2025-3-30 14:39:57 | 只看該作者
https://doi.org/10.2991/978-94-91216-11-4Artificial Intelligence; Knowledge bases; Logic
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發(fā)表于 2025-3-30 20:05:58 | 只看該作者
Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal,Contextual and Causal Inference978-94-91216-11-4Series ISSN 1877-3273 Series E-ISSN 1877-3281
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發(fā)表于 2025-3-30 22:57:18 | 只看該作者
Knowledge Representation Using Formal Logiccontextual knowledge, wemust discuss representation of temporal knowledge (as well as, to a certain extent, spatialknowledge) . . . and before that, we must address knowledge representation in general.
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發(fā)表于 2025-3-31 04:38:33 | 只看該作者
Temporal Reasoningnference, but experienceshows that this is not an optimal approach, mainly because such an approach leads toextreme inefficiencies of inference control. Thus, in this section and the following ones wewill consider specific logical formalisms recently proposed for reasoning about time andspace.?
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