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首页> 外文期刊>Journal of Universal Computer Science >Knowledge Geometry in Phenomenon Perception and Artificial Intelligence
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Knowledge Geometry in Phenomenon Perception and Artificial Intelligence

机译：现象感知和人工智能的知识几何

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Artificial Intelligence (AI) pervades industry, entertainment, transportation, finance, and health. It seems to be in a kind of golden age, but today AI is based on the strength of techniques that bear little relation to the thought mechanism. Contemporary techniques of machine learning, deep learning and case-based reasoning seem to be occupied with delivering functional and optimized solutions, leaving aside the core reasons of why such solutions work. This paper, in turn, proposes a theoretical study of perception, a key issue for knowledge acquisition and intelligence construction. Its main concern is the formal representation of a perceived phenomenon by a casual observer and its relationship with machine intelligence. This work is based on recently proposed geometric theory, and represents an approach that is able to describe the inuence of scope, development paradigms, matching process and ground truth on phenomenon perception. As a result, it enumerates the perception variables and describes the implications for AI.
机译：人工智能（AI）遍及行业，娱乐，交通，金融和健康。它似乎处于一种黄金时代，但今天AI基于与思想机制几乎没有关系的技术的力量。当代机器学习技术，深度学习和基于案例的推理似乎被提供功能和优化的解决方案占用，抛开了这种解决方案工作的核心原因。本文反过来提出了对知识获取和智力建设的关键问题的理论研究。其主要关注是通过休闲观察者及其与机器智能的关系来表示感知现象的正式代表。这项工作基于最近提出的几何理论，代表了一种能够描述范围，发展范式，匹配过程和地面真实性对现象感知的影响的方法。因此，它枚举了感知变量，并描述了对AI的影响。

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