A computational theory of motor learning

A computational theory of motor learning

In this paper we present a computational theory of human motor performance and learning. The theory is implemented as a running AI system called MAGGIE. Given a description of a desired movement as input, the system generates simulated motor behavior as output. The theory states that skills are encoded as moror s c h e m , which specify the positions and velocities of a limb at selected points ...

Computational Learning Theory

Valiant introduces a precise computational model for concept learning. Concept learning is about learning to decide whether a certain data belongs to a certain concept (is this a table? Is there an elephant in the data?). The paper is the birth of PAC-learning (PAC = Probably Approximately Correct). What is a concept? A concept is simply a subset of some domain. A concept comes from a some conc...

Outline for a Theory of Motor Learning

This paper outlines a new theory of motor learning. The theory is constrained by the anatomy and physiology of sensorimotor pathways through the cerebellum, motor cortex, brainstem and spinal cord. It also draws upon recent knowledge regarding cellular and molecular properties and receives insight from the results of learning experiments with artificial neural networks. The zonal organization t...

A neuropsychological theory of motor skill learning.

This article describes a neuropsychological theory of motor skill learning that is based on the idea that learning grows directly out of motor control processes. Three motor control processes may be tuned to specific tasks, thereby improving performance: selecting spatial targets for movement, sequencing these targets, and transforming them into muscle commands. These processes operate outside ...

Computational Learning Theory