Using genetic programming and decision trees for generating structural descriptions of four bar mechanisms

Authors:
Anikó Ekárt;András Márkus
Affiliations:
Computer and Automation Research Institute, Hungarian Academy of Sciences, Budapest, Hungary;Computer and Automation Research Institute, Hungarian Academy of Sciences, Budapest, Hungary
Venue:
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Year:
2003

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Abstract

Four bar mechanisms are basic components of many important mechanical devices. The kinematic synthesis of four bar mechanisms is a difficult design problem. A novel method that combines the genetic programming and decision tree learning methods is presented. We give a structural description for the class of mechanisms that produce desired coupler curves. Constructive induction is used to find and characterize feasible regions of the design space. Decision trees constitute the learning engine, and the new features are created by genetic programming.