S-Learning: A Biomimetic Algorithm for Learning, Memory, and Control in Robots

Abstract

S-learning is a sequence-based learning algorithm patterned on human motor behavior. Discrete-time and quantized sensory information is amassed in real-time to form a dynamic model of the system being controlled and its environment. No explicit model is provided a priori, nor any hint about what the structure of the model might be. As the core of a Brain-Emulating Cognition and Control Architecture (BECCA), S-Learning provides a mechanism for human-inspired learning, memory, and control in machines. In a simulation of a point-to-point reaching task, S-Learning demonstrates several attributes of human motor behavior, including learning through exploration and task transfer.