Evolutionary Multi-Agent Computing in Inverse Problems


  • Krzysztof Wróbel AGH University of Science and Technology
  • Paweł Torba AGH University of Science and Technology
  • Maciej Paszyński AGH University of Science and Technology
  • Aleksander Byrski AGH University of Science and Technology




The paper tackles the application of evolutionary multi-agent computing to solving inverse problems. High costs of fitness function call become a major difficulty when approachingthese problems with population-based heuristics, however evolutionary agent-based systems (EMAS)turn out to reduce the fitness function calls, which makes them a  possible weapon of choicefor them. The paper recalls the basics of EMAS and describes the considered problem (Step and Flash Imprint Lithography),later showing convincing results, that EMAS turns out to be more effective than classical evolutionary algorithm.


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How to Cite

Wróbel, K., Torba, P., Paszyński, M., & Byrski, A. (2013). Evolutionary Multi-Agent Computing in Inverse Problems. Computer Science, 14(3), 367. https://doi.org/10.7494/csci.2013.14.3.367




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