Abstract
We explore incremental assimilation of new knowledge by sequential
learning. Of particular interest is how a network of many knowledge
layers can be constructed in an on-line manner, such that the learned
units represent building blocks of knowledge that serve to compress
the overall representation and facilitate transfer. We motivate the
need for many layers of knowledge, and we advocate sequential learning
as an avenue for promoting the construction of layered knowledge
structures. Finally, our novel STL algorithm demonstrates a method
for simultaneously acquiring and organizing a collection of concepts
and functions as a network from a stream of unstructured information.
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