摘要翻译：
机器智能(MI)的理论分析有助于定义理论和应用人工智能(AI)的通用平台。本文的目标是建立规范的定义，以辅助强人工智能和弱人工智能的语用研究。描述机器智能的认识论特征包括智能行为之间的关系、智能与非智能的机器特征、可观察实体与不可观察实体以及智能的分类。本文还建立了MI测试的效率和准确度的代数定义，以此作为MI测试的质量度量。论文的最后一部分是关于传统认识论和这里所描述的MI认识论的学习过程。所提出的关于MI的观点与黑格尔一元论认识论正相关，并有助于将理想主义的讨论与人工智能理论结合起来，尤其是在一个局部的参考框架中。
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英文标题：
《Elementary epistemological features of machine intelligence》
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作者：
Marko Horvat
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最新提交年份：
2017
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分类信息：

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：
  Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of intelligence. The paper also establishes algebraic definitions of efficiency and accuracy of MI tests as their quality measure. The last part of the paper addresses the learning process with respect to the traditional epistemology and the epistemology of MI described here. The proposed views on MI positively correlate to the Hegelian monistic epistemology and contribute towards amalgamating idealistic deliberations with the AI theory, particularly in a local frame of reference.
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PDF链接：
https://arxiv.org/pdf/0812.0885