Reconstructive derivational analogy: A machine learning approach to automating redesign

Abstract

This paper describes current research toward automating the redesign process. In redesign, a working design is altered to meet new problem specifications. This process is complicated by interactions between different parts of the design, and many researchers have addressed these issues. An overview is given of a large design tool under development, the Circuit Designer's Apprentice. This tool integrates various techniques for reengineering existing circuits so that they meet new circuit requirements. The primary focus of the paper is one particular technique being used to reengineer circuits when they cannot be transformed to meet the new problem requirements. In these cases, a design plan is automatically generated for the circuit, and then replayed to solve all or part of the new problem. This technique is based upon the derivational analogy approach to design reuse. Derivational Analogy is a machine learning algorithm in which a design plan is saved at the time of design so that it can be replayed on a new design problem. Because design plans were not saved for the circuits available to the Circuit Designer's Apprentice, an algorithm was developed that automatically reconstructs a design plan for any circuit. This algorithm, Reconstructive Derivational Analogy, is described in detail, including a quantitative analysis of the implementation of this algorithm.

Design rationale: Researching under uncertainty

“…JANUS (Fischer et al, 1996) Kitchen design JANUS was evaluated informally with designers and computer users at different levels performing learning and design tasks. Reconstructive Derivational Analogy (RDA; Britt & Glagowski, 1996) Design process is replayed using new requirements to create a new design CPU and actual time were compared for a representative set of simple problems. It was not stated if this was tested using more than one designer.…”

A foundation for machine learning in design

“…Detailing to reconstruct design history. Unlike BOG-ART and ARGO, which rely on records of past design decisions in the form of a design plan, CDA first reconstructs from a similar solution a design plan using predefined rules (Britt & Glagowski, 1996). So while BOGART uses a derivational analogy to solve a new design problem, CDA uses a reconstructive derivational analogy (RDA) algorithm to automatically reconstruct design plan(s) from a large collection of past working design(s).…”