机器智能的基本认识论特征
Elementary epistemological features of machine intelligence
摘要：
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）的公共平台。本文的目标是建立规范的定义，可以帮助语用研究在强和弱人工智能。描述了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、可观察与不可观察的实体以及智能的分类。本文还建立了多元智能测试的效率和准确性的代数定义作为其质量度量。文章的最后一部分从传统的认识论和多元智能的认识论两个方面论述了学习过程。建议的意见MI积极相关的黑格尔一元论认识论，并有助于融合理想主义的审议与人工智能理论，特别是在当地的参考框架。
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
