In this paper we present a system that uses its underlying physiology, a hierarchical memory and a collection of memory management algorithms to learn concepts as cases and to bui...
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intellig...
Policy Reuse is a method to improve reinforcement learning with the ability to solve multiple tasks by building upon past problem solving experience, as accumulated in a Policy Li...
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...