Sciweavers

Share
AAI
2005

Machine Learning in Hybrid Hierarchical and Partial-Order Planners for Manufacturing Domains

9 years 5 months ago
Machine Learning in Hybrid Hierarchical and Partial-Order Planners for Manufacturing Domains
The application of AI planning techniques to manufacturing systems is being widely deployed for all the tasks involved in the process, from product design to production planning and control. One of these problems is the automatic generation of control sequences for the entire manufacturing system in such a way that final plans can be directly used as the sequential control programs which drive the operation of manufacturing systems. Hybis is a hierarchical and nonlinear planner whose goal is to obtain partially ordered plans at such a level of detail that they can be used as sequential control programs for manufacturing systems. Currently, those sequential control programs are being generated by hand using modelling tools. This document describes a work whose aim is to improve the efficiency of solving problems with Hybis by using machine learning techniques. It implements a deductive learning method that is able to automatically acquire control knowledge (heuristics) by generating bou...
Susana Fernández, Ricardo Aler, Daniel Borr
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2005
Where AAI
Authors Susana Fernández, Ricardo Aler, Daniel Borrajo
Comments (0)
books