Reliable plan selection by intelligent machines /
This book derives techniques which allow reliable plans to be automatically selected by intelligent machines. It concentrates on the uncertainty analysis of candidate plans so that a highly reliable candidate may be identified and used. For robotic components, such as a particular vision algorithm f...
| Main Author: | |
|---|---|
| Other Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore ; River Edge, NJ :
World Scientific,
1995.
|
| Series: | Series in intelligent control and intelligent automation ;
v. 1. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | This book derives techniques which allow reliable plans to be automatically selected by intelligent machines. It concentrates on the uncertainty analysis of candidate plans so that a highly reliable candidate may be identified and used. For robotic components, such as a particular vision algorithm for pose estimation or a joint controller, methods are explained for directly calculating the reliability. However, these methods become excessively complex when several components are used together to complete a plan. Consequently, entropy minimization techniques are used to estimate which complex tasks will be performed reliably. The book first develops tools for directly calculating the reliability of sub-systems, and methods of using entropy minimization to greatly facilitate the analysis are explained. Since these sub-systems are used together to accomplish complex tasks, the book then explains how complex tasks can be efficiently evaluated. |
|---|---|
| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (ix, 154 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 147-152) and index. |
| ISBN: | 9789812830791 (electronic bk.) 9812830790 (electronic bk.) |