提出自动构建抽象层次的原型框架，助力智能行为建模。
Reducing Diversity to Generate Hierarchical Archetypes
- 基于特定原型设计自动构建抽象层次的框架
- 通过数学证明验证框架有效性
- 适合研究认知架构与智能系统构建的学者
人工智能领域很少关注基础构建模块的发展：即自动构建抽象层次的框架、方法或算法。这在构建智能行为中至关重要，近期神经科学研究已明确揭示这一点。本文提出一种基于原型的框架，可自动生成构造性原型的层次结构，作为生成抽象层次的理论。我们假设存在具备特定特性的原型，并以此为基础构建框架。通过数学定义与证明，验证了该框架的有效性。最后，我们给出该框架潜在应用的若干洞察及预期成果。
原文摘要 · Abstract (English)
The Artificial Intelligence field seldom address the development of a fundamental building piece: a framework, methodology or algorithm to automatically build hierarchies of abstractions. This is a key requirement in order to build intelligent behaviour, as recent neuroscience studies clearly expose. In this paper we present a primitive-based framework to automatically generate hierarchies of constructive archetypes, as a theory of how to generate hierarchies of abstractions. We assume the existence of a primitive with very specific characteristics, and we develop our framework over it. We prove the effectiveness of our framework through mathematical definitions and proofs. Finally, we give a few insights about potential uses of our framework and the expected results.
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