Search
 
loader loading subjects...
cover
Comparison of Data Amount for Representing Decision Making Policy
Ryuichi Ueda
26 - 35
10.3233/978-1-58603-887-8-26
Intelligent Autonomous Systems 10
Abstract

This paper deals with the problem of how to implement software controller for a robot with a small amount of random access memory (RAM) on its computer. This problem is essentially different from how to solve it with a small amount of RAM. This paper purely compares the trade-off between memory use and performance of a controller. We found that policies that are compressed by vector quantization have an efficient representation.

$35.00 / €27.50 / £22.00
Add PDF to cart