摘要翻译:
智能体的判断依赖于感知和先前的知识。假定先前的知识依赖于知觉,我们可以说判断依赖于知觉。那么,如果判断依赖于知觉,那么智能体能判断出他们有相同的知觉吗?简而言之,这是通过本文件解决的悖论。通过对这一悖论的阐释,我们发现,要在交际中达成一致,并不一定要求双方具有相同的知觉,而必须有知觉的对应。对这一悖论的尝试解决揭示了判断这一问题的潜在不确定性,从而支持了对这一问题的怀疑观点。此外,将感知与智能联系起来,同样的不确定性是通过判断一个智能体与不一定来自同类的其他智能体相比的智能水平来继承的(例如,机器智能与人类智能相比)。利用一个关于感知和行动的简单数学模型,开发了一个工具来构造场景,并从数学上解决这个问题,从而根据数学定义的属性系统地得出结论。当谈到形式化时,哲学论点和观点变得更加可见和明确。
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英文标题:
《Perception Lie Paradox: Mathematically Proved Uncertainty about Humans
Perception Similarity》
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作者:
Ahmed M. Mahran
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最新提交年份:
2012
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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:
Agents' judgment depends on perception and previous knowledge. Assuming that previous knowledge depends on perception, we can say that judgment depends on perception. So, if judgment depends on perception, can agents judge that they have the same perception? In few words, this is the addressed paradox through this document. While illustrating on the paradox, it's found that to reach agreement in communication, it's not necessary for parties to have the same perception however the necessity is to have perception correspondence. The attempted solution to this paradox reveals a potential uncertainty in judging the matter thus supporting the skeptical view of the problem. Moreover, relating perception to intelligence, the same uncertainty is inherited by judging the level of intelligence of an agent compared to others not necessarily from the same kind (e.g. machine intelligence compared to human intelligence). Using a proposed simple mathematical model for perception and action, a tool is developed to construct scenarios, and the problem is addressed mathematically such that conclusions are drawn systematically based on mathematically defined properties. When it comes to formalization, philosophical arguments and views become more visible and explicit.
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PDF链接:
https://arxiv.org/pdf/1202.4174