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Evolution, emergence, semiosis: components of the model for intelligent system

机译:进化,出现,符号化:智能系统模型的组成部分

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The discussion of intelligent system usually starts with issues of defining intelligence as a set of skills, but always ends with specifying the mechanisms of learning. It is important to address the issue of differences and similarities between the techniques of computational/control learning processes (very similar to the processes of semiosis) and biological learning including evolution of species where the resemblance with semiosis is less obvious. We would like to attract attention to the theory of multilevel processes of evolution which are interpreted in this paper as multiresolutional processes of evolution. Novel explanations are preposed for numerous paradoxes known in the area of computational and biological learning including evolution of species. The direct linkage is demonstrated of learning processes and the development of decision-making mechanisms for single and multiple agents.
机译:关于智能系统的讨论通常始于将智力定义为一组技能的问题,但始终以指定学习机制作为结尾。重要的是要解决计算/控制学习过程的技术(非常类似于符号学的过程)与生物学学习(包括物种演化,其中与符号学的相似性不太明显)之间的差异和相似性问题。我们想吸引人们注意进化的多级过程理论,本文将其解释为进化的多分辨率过程。对于在计算和生物学习领域(包括物种进化)中已知的众多悖论提出了新颖的解释。直接联系证明了学习过程以及单个和多个代理的决策机制的发展。

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