Generating languages of solid models
SMA '93 Proceedings on the second ACM symposium on Solid modeling and applications
RoboCup: The Robot World Cup Initiative
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Concurrent programming: the Java programming language
Concurrent programming: the Java programming language
Evolutionary Design by Computers with CDrom
Evolutionary Design by Computers with CDrom
Intelligent Systems for Engineering: A Knowledge-Based Approach
Intelligent Systems for Engineering: A Knowledge-Based Approach
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Algorithms
Genetic design of antennas and electronic circuits
Genetic design of antennas and electronic circuits
Evolutionary Body Building: Adaptive Physical Designs for Robots
Artificial Life
Assembly synthesis with subassembly partitioning for optimal in-process dimensional adjustability
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Hierarchical component-based representations for evolving microelectromechanical systems designs
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
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This paper presents an approach to the automatic generation of electromechanical engineering designs. We apply messy genetic algorithm (GA) optimization techniques to the evolution of assemblies composed of LegoTM structures. Each design is represented as a labeled assembly graph and is evaluated based on a set of behavior and structural equations. The initial populations are generated at random, and design candidates for subsequent generations are produced by user-specified selection techniques. Crossovers are applied by using cut and splice operators at the random points of the chromosomes; random mutations are applied to modify the graph with a certain low probability. This cycle continues until a suitable design is found. The research contributions in this work include the development of a new GA encoding scheme for mechanical assemblies (Legos), as well as the creation of selection criteria for this domain. Our eventual goal is to introduce a simulation of electromechanical devices into our evaluation functions. We believe that this research creates a foundation for future work and it will apply GA techniques to the evolution of more complex and realistic electromechanical structures.