The Evolution of Concept-Acquisition based on Developmental Psychology
Hui Wei

TL;DR
This paper explores how developmental psychology insights, particularly Karmiloff-Smith's Representation Redescription, can inform the construction of more adaptable and rich conceptual systems in artificial intelligence using an object-oriented approach.
Contribution
It introduces a formal semantic model based on object-oriented principles to implement the concept acquisition process inspired by developmental psychology.
Findings
Proposes a formal semantic model for concept acquisition.
Reinterprets Representation Redescription within an object-oriented framework.
Lays groundwork for building adaptable AI conceptual systems.
Abstract
A conceptual system with rich connotation is key to improving the performance of knowledge-based artificial intelligence systems. While a conceptual system, which has abundant concepts and rich semantic relationships, and is developable, evolvable, and adaptable to multi-task environments, its actual construction is not only one of the major challenges of knowledge engineering, but also the fundamental goal of research on knowledge and conceptualization. Finding a new method to represent concepts and construct a conceptual system will therefore greatly improve the performance of many intelligent systems. Fortunately the core of human cognition is a system with relatively complete concepts and a mechanism that ensures the establishment and development of the system. The human conceptual system can not be achieved immediately, but rather must develop gradually. Developmental psychology…
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Taxonomy
TopicsChild and Animal Learning Development · Visual and Cognitive Learning Processes · Science Education and Pedagogy
