Modeling Single-Task Performance Improvement Using EPIC-Soar

Ninth Midwest Artificial intelligence and Cognitive Science Conference

Volume

Ninth Midwest Artificial intelligence and Cognitive Science Conference

Contents

Difficulties with part oriented solid modeling tools have motivated the development of a derivationbased solid modeling system to aid in preliminary submarine design tasks. The projected system is a graphically editable geometric rule system based on Extended Pattern Grammars with Variables (EPGVs). This paper reviews relevant characteristics of Boundary Representation Modelers, Featurebased Modelers and Extended Pattern Grammars, then establishes a fundamental relationship begveen the Inference Dependency Graph that is constructed during an EPGV derivation and a parametric system Feature tree. The primary technique involved with editing an EPGV derived model is identified with Dependency Driven Backtracking, and a description of the process is presented.