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Titlebook: Engineering General Intelligence, Part 2; The CogPrime Archite Ben Goertzel,Cassio Pennachin,Nil Geisweiller Book 2014 Atlantis Press and t

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樓主: radionuclides
11#
發(fā)表于 2025-3-23 13:23:09 | 只看該作者
12#
發(fā)表于 2025-3-23 15:53:59 | 只看該作者
13#
發(fā)表于 2025-3-23 18:10:42 | 只看該作者
14#
發(fā)表于 2025-3-24 01:12:47 | 只看該作者
Knowledge Representation Using the AtomspaceCogPrime’s knowledge representation must be considered on two levels: implicit and explicit. This chapter considers mainly explicit knowledge representation, with a focus on representation of declarative knowledge.
15#
發(fā)表于 2025-3-24 02:29:23 | 只看該作者
16#
發(fā)表于 2025-3-24 09:45:43 | 只看該作者
17#
發(fā)表于 2025-3-24 11:51:35 | 只看該作者
Attention AllocationThe critical factor shaping real-world general intelligence is resource constraint.
18#
發(fā)表于 2025-3-24 18:40:46 | 只看該作者
19#
發(fā)表于 2025-3-24 19:33:11 | 只看該作者
Perceptual and Motor HierarchiesHaving discussed declarative, attentional, intentional and procedural knowledge, we are left only with sensorimotor and episodic knowledge to complete our treatment of the basic CogPrime “cognitive cycle” via which a CogPrime system can interact with an environment and seek to achieve its goals therein.
20#
發(fā)表于 2025-3-25 02:31:53 | 只看該作者
Integrating CogPrime with a Compositional Spatiotemporal Deep Learning NetworkMany different approaches to “l(fā)ow-level” perception and action processing are possible within the overall CogPrime framework. We discussed several in the previous chapter, all elaborations of the general hierarchical pattern recognition approach.
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