Learning Based on CC1 and CC4 Neural Networks
This work addresses the challenge of building more human-like learning systems for AI researchers, but it appears incremental as it applies existing networks to a conceptual framework.
The authors tackled the problem of designing a general learning system by proposing three agents for sensory, short-term, and long-term memory, inspired by human cognition, and investigated CC1 and CC4 networks as models for short-term and sensory memory.
We propose that a general learning system should have three kinds of agents corresponding to sensory, short-term, and long-term memory that implicitly will facilitate context-free and context-sensitive aspects of learning. These three agents perform mututally complementary functions that capture aspects of the human cognition system. We investigate the use of CC1 and CC4 networks for use as models of short-term and sensory memory.