Жалпы жинақтаушы оқу: жасанды интеллекттегі білімнің қалыптасуы

cumulative learning in artificial intelligence

Cumulative learning is the cognitive process by which we accumulate and improve knowledge and abilities that serve as building blocks for subsequent cognitive development. A primary benefit of such is that it consolidates knowledge one has obtained through experience, and allows the facilitation of further learning through analogical knowledge transfer. It is a concept that has been widely written about in psychological literature, with scholars particularly drawing attention to the fact it allows for the incremental increase in scope of ability and knowledge., without damaging pre existing skills. More meaningfully constructed knowledge can be better reserved for future use. This theory serves as an alternative approach to maturational theories such as the model proposed by Jean Piaget concerning intellectual and learning development.

American psychologist Robert M. Gagne first introduced the concept of cumulative learning in 1968 on the basis that intellectual skills can be broken down into simpler ones. His model proposed that new learning builds upon prior learning and is dependent on the combination of previously acquired knowledge. The core assumption underlying the concept is that the learning of humans is cumulative by nature, so learned knowledge is consolidated and reproduced for further learning situations. In this framework, instead of the content and concepts of the task, the learning hierarchies address intellectual skills and strategies. He demonstrated this in the case of children's performance on conservation tasks over time. Cumulative learning consolidates the knowledge one has obtained through experiences, allowing it to be reproduced and exploited for subsequent learning situations through cumulative interaction between prior knowledge and new information. Children construct new knowledge by updating and revising previous beliefs, learning through observations, participation and imitation. They provide learning opportunities as if a test doesn't go as planned, a researcher can use the information gained to adapt the methods used in the next experiment. However, relying on the naturally occurring replication of experimental research may not suffice to promote cumulative learning because interventions and outcomes measures are different across disparate contexts. Whilst this may be true, it is clear that the concept itself is prevalent in cognitive development as illustrated through the ways children learn and use new knowledge to inform future situations.