Application of artificial intelligence (Al) has been a topic of interest among researchers for the past decade or more. Years of research in the commercial application of Al, availability of hardware support for Al application and affordability of software and hardware has generated a lot of interest in this field and brought this technology within the reach of micro-computer based users. The commercial impact of AI is due to expert systems (ESs). ES technology is a collection of methods and techniques for constructing human-machine systems with specialized problem solving expertise.
This project explores the application of ESs in landscape architecture by developing a prototype ES and testing implications of its use with designers while working on a hypothetical problem in a studio environment. The development process helps identify the typical difficulties of such an application, to uncover technical problems, and to identify areas needing further research.
The project aims at building an ES that provides very limited preliminary data and design guidelines to initialize the design process and keeps track of the most fundamental issues necessary for planning, thus acting as an expert and assistant simultaneously. The idea is to explore the possibility of applying ESs to facilitate the design process so that designers may concentrate on other important aspects of design which include intuitive judgement about qualitative aspects. / Master of Landscape Architecture
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/43899 |
| Date | 24 July 2012 |
| Creators | Kulkarni, Nitin Y. |
| Contributors | Landscape Architecture, Johnson, Benjamin C., Rakes, Terry R., Nutter, Jane Terry |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis, Text |
| Format | vi [i.e. viii], 146 leaves, BTD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | OCLC# 20801868, LD5655.V855_1989.K865.pdf |
Page generated in 0.0021 seconds