Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.662724
Title: Knowledge-based design support and inductive learning
Author: Tang, M. X.
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 1995
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Abstract:
In order to incorporate inductive learning techniques into a knowledge-based design model and an integrated knowledge-based design support system architecture, the computational techniques for developing a knowledge-based design support system architecture and the role of inductive learning in AI-based design are investigated. This investigation gives a background to the development of an incremental learning model for design suitable for a class of design tasks whose structures are not well known initially. This incremental learning model for design is used as a basis to develop knowledge-based design support system architecture that can be used as a kernel for knowledge-based design applications. This architecture integrates a number of computational techniques to support the representation and reasoning of design knowledge. In particular, it integrates a blackboard control system with an assumption-based truth maintenance system in an object-oriented environment to support the exploration of multiple design solutions by supporting the exploration and management of design contexts. As an integral part of this knowledge-based design support architecture, a design concept learning system utilising a number of unsupervised inductive learning techniques is developed. This design concept learning system combines concept formation techniques with design heuristics as background knowledge to build a design concept tree from raw data or past design examples. The effectiveness of this knowledge-based design support architecture and the design concept learning system is demonstrated through a realistic design domain, the design of small-molecule drugs one of the key tasks of which is to identify a pharmacophore description (the structure of a design problem) from known molecule examples. In this thesis, knowledge-based design and inductive learning techniques are first reviewed. Based on this review, an incremental learning model and an integrated architecture for intelligent design support are presented.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.662724  DOI: Not available
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