Thomas Weise (汤卫思)

A professor at Hefei University.

Genetic Programming (GP) means to perform evolutionary search in a tree-based search space. Often, such trees are designed to represent programs of sorts, sometimes classifiers. This field is somehow in decline with the advent of deep learning. However, there are quite a few interesting things that can be done.

Algorithm Synthesis

For me, the most interesting topic of Genetic Programming was always algorithm synthesis. Here, the goal is to use optimization algorithms to construct new algorithms. Matter of fact, combining GP withFFAyields very good performance when constructing discrete algorithms. Sadly, I never had time to follow this line of research more in depth, but I hope to do so in the future.

  • Thomas Weise (汤卫思), Mingxu WAN (万明绪), Ke TANG (唐珂), and Xin YAO (姚新): Evolving Exact Integer Algorithms with Genetic Programming. IEEE Congress on Evolutionary Computation (CEC'2014), part of the World Congress on Computational Intelligence (WCCI'2014), pages 1816-1823, July 6-11, 2014, Beijing, China. Los Alamitos, CA, USA: IEEE Computer Society Press.
    GP, FFA, more infos.
  • Thomas Weise (汤卫思), Mingxu WAN (万明绪), Ke TANG (唐珂), Pu WANG, Alexandre Devert, and Xin YAO (姚新): Frequency Fitness Assignment. IEEE Transactions on Evolutionary Computation (IEEE-TEVC) 18(2):226-243. April 2014.
    FFA, GP, more infos.
  • Thomas Weise (汤卫思) and Ke TANG (唐珂): Evolving Distributed Algorithms with Genetic Programming. IEEE Transactions on Evolutionary Computation (TEVC) 16(2):242-265. April 2012.
    GP, more infos.
  • Mingxu WAN (万明绪), Thomas Weise (汤卫思), and Ke TANG (唐珂): Novel Loop Structures and the Evolution of Mathematical Algorithms. 14th European Conference on Genetic Programming (EuroGP'2011), April 27-29, 2011, Torino, Italy, Lecture Notes in Computer Science (LNCS), volume 6621/2011, pages 49-60. Berlin, Germany: Springer-Verlag GmbH.
    GP, more infos.
  • Thomas Weise (汤卫思) and Michael Zapf: Evolving Distributed Algorithms with Genetic Programming: Election. 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation (GEC'2009), June 12-14, 2009, Shanghai, China, pages 577-584. New York, NY, USA ACM Press.
    GP, more infos.
  • Thomas Weise (汤卫思): Evolving Distributed Algorithms with Genetic Programming. PhD Thesis published in May 2009 at the Department of Electrical Engineering and Computer Science (FB16) of the University of Kassel in Kassel, Germany.
    GP, more infos.
  • Thomas Weise (汤卫思), Michael Zapf, Mohammad Ullah Khan, and Kurt Geihs: Combining Genetic Programming and Model-Driven Development. International Journal of Computational Intelligence and Applications (IJCIA), 8(1):37-52. March 2009.
    GP, more infos.
  • Michael Zapf and Thomas Weise (汤卫思): Can Solutions Emerge? 3rd International Workshop on Self-Organizing Systems (IWSOS'2008), December 10-12, 2008, Vienna, Austria. Lecture Notes in Computer Science (LNCS), volume 5343/2008, pages 299-304. Berlin, Germany: Springer-Verlag GmbH.
    GP, more infos.
  • Michael Zapf and Thomas Weise (汤卫思): Applicability of Emergence Engineering to Distributed Systems Scenarios. 6th European Workshop on Multi-Agent Systems (EUMAS'2008), December 18-19, 2008, Bath, UK.
    GP, more infos.
  • Thomas Weise (汤卫思), Michael Zapf, and Kurt Geihs: Evolving Proactive Aggregation Protocols. 11th European Conference on Genetic Programming (EuroGP'2008), March 26-28, 2008, Naples, Italy, Lecture Notes in Computer Science (LNCS) volume 4971/2008, pages 254-265. Berlin, Germany: Springer-Verlag GmbH.
    GP, more infos.
  • Michael Zapf and Thomas Weise (汤卫思): Offline Emergence Engineering For Agent Societies. 5th European Workshop on Multi-Agent Systems (EUMAS'2007), December 14, 2007, Hammamet, Tunesia.
    GP, more infos.
  • Thomas Weise (汤卫思), Michael Zapf, and Kurt Geihs: Rule-based Genetic Programming. 2nd International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS'2007), December 10-12, 2007, Budapest, Hungary, pages 8-15. Piscataway, NJ, USA: IEEE Computer Society.
    GP, more infos.
  • Thomas Weise (汤卫思), Michael Zapf, Mohammad Ullah Khan, and Kurt Geihs: Genetic Programming meets Model-Driven Development. 7th International Conference on Hybrid Intelligent Systems (HIS'2007), September 17-19, 2007, Kaiserslautern, Germany, pages 332-335. Piscataway, NJ, USA: IEEE Computer Society.
    GP, more infos.
  • Thomas Weise (汤卫思), Kurt Geihs, and Philipp Andreas Baer: Genetic Programming for Proactive Aggregation Protocols. 8th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA'2007), April 11-17, 2007, Warsaw, Poland, Part I, Lecture Notes in Computer Science (LNCS), volume 4431/2007, pages 167-173. Berlin, Germany: Springer-Verlag GmbH.
    GP, more infos.
  • Thomas Weise (汤卫思) and Kurt Geihs: DGPF — An Adaptable Framework for Distributed Multi-Objective Search Algorithms Applied to the Genetic Programming of Sensor Networks. 2nd International Conference on Bioinspired Optimization Methods and their Applications (BIOMA'2006), October 9-10, 2006, Ljubljana, Slovenia, pages 157-166.
    GP, more infos.
  • Thomas Weise (汤卫思) and Kurt Geihs: Genetic Programming Techniques for Sensor Networks. Tagungsband: 5. GI/ITG KuVS Fachgesprächs “Drahtlose Sensornetze”, July 17-18, 2006, Stuttgart, Germany, pages 21-25.
    GP, more infos.

Classification

Classification is another classical application area of Genetic Programming. Since many traditional classification approaches use decision trees in one way or another and GP means searching the space of trees, this comes very natural.

  • Thomas Weise (汤卫思), Mingxu WAN (万明绪), Ke TANG (唐珂), Pu WANG, Alexandre Devert, and Xin YAO (姚新): Frequency Fitness Assignment. IEEE Transactions on Evolutionary Computation (IEEE-TEVC) 18(2):226-243. April 2014.
    FFA, GP, more infos.
  • Pu WANG, Ke TANG (唐珂), Thomas Weise (汤卫思), Edward P.K. Tsang (曾炳均), and Xin YAO (姚新): Multiobjective Genetic Programming for Maximizing ROC Performance. Neurocomputing 125:102-118. February, 2014.
    GP, more infos.
  • Pu WANG, Thomas Weise (汤卫思), and Raymond Chiong: Novel Evolutionary Algorithms for Supervised Classification Problems: An Experimental Study. Evolutionary Intelligence 4(1):3-16. March 2011.
    GP, more infos.

Updated: