摘要翻译:
计算机实现“幽默感”需要创造一种算法来解决“语言问题”,即识别连续序列的多语义图像的问题。该算法可在神经网络的Hopfield模型中实现。
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英文标题:
《Computer Model of a "Sense of Humour". II. Realization in Neural
Networks》
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作者:
I. M. Suslov (P.L.Kapitza Institute for Physical Problems, Moscow,
Russia)
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最新提交年份:
2007
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分类信息:
一级分类:Quantitative Biology 数量生物学
二级分类:Neurons and Cognition 神经元与认知
分类描述:Synapse, cortex, neuronal dynamics, neural network, sensorimotor control, behavior, attention
突触,皮层,神经元动力学,神经网络,感觉运动控制,行为,注意
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一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要:
The computer realization of a "sense of humour" requires the creation of an algorithm for solving the "linguistic problem", i.e. the problem of recognizing a continuous sequence of polysemantic images. Such algorithm may be realized in the Hopfield model of a neural network after its proper modification.
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PDF链接:
https://arxiv.org/pdf/0711.2061