- author = "Maxim Peysakhov and William C. Regli",
- title = "Using assembly representations to enable evolutionary design of Lego structures",
- journal = "Artificial Intelligence for Engineering Design, Analysis and Manufacturing",
- year = "2003",
- volume = "17",
- number = "2",
- pages = "155--168",
- month = may,
- keywords = "genetic algorithms, genetic programming, EHW, Assembly Modeling, Computer-Aided Design, CAD, Engineering Design, Evolutionary Design, Lego, toy building blocks",
- ISSN = "0890-0604",
- publisher = "Cambridge University Press",
-
URL = "
https://www.cambridge.org/core/journals/ai-edam/article/abs/using-assembly-representations-to-enable-evolutionary-design-of-lego-structures/94CB61C095F6C2AC0942452E2465E893",
-
DOI = "
10.1017/S0890060403172046",
- size = "14 pages",
- abstract = "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 Lego 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.",
-
notes = "AI EDAM AIE172-4.
Geometric and Intelligent Computing Laboratory, Department of Computer Science, Drexel University, Philadelphia, Pennsylvania 19104, USA",
