When thinking about distributed systems, we usually either think about the applications and services they can offer to us or technological aspects, protocols like TCP/IP. Distributed algorithms, however, are an extremely underrated topic. They offer services such as leader election, mutual exclusion, or data aggregation, which are usually located somewhere "under the hood" in radio networks, network shares, or sensor networks. Roughly from 2005 to 2015, Dr. Weise has actively researched the question "Can we automatically synthesize such algorithms?" or, more generally, "Can a computer invent an actual, non-trivial program?"
In other words, this strand of our research is focused on Inductive Program Synthesis, i.e., the automatic generation of programs which can compute exactly the wanted outputs for a set of specified input examples. Genetic programming (GP) is a type of evolutionary algorithm, i.e., an optimization method, whose name implies that it might be suitable for this. Yet it has been applied mainly to different problems – or very coarse interpretations of the term "program." In his work, Dr. Weise investigated several improvements of GP, including new representations and special fitness assignment procedures. The work led to his award-winning PhD thesis, but was later also extended to the synthesis of exact integer mathematical algorithms. It led to the automatic evolution of real, non-trivial, complex algorithms, containing loops and conditionals. Without any "cheating" such as gently guiding the optimization procedure into the right direction.
Publications
Thomas Weise, Mingxu Wan, Ke Tang, and Xin Yao. Evolving Exact Integer Algorithms with Genetic Programming. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC'14), Proceedings of the 2014 World Congress on Computational Intelligence (WCCI'14), pages 1816-1823, Beijing, China: Beijing International Convention Center (BICC), July 6-11, 2014. Los Alamitos, CA, USA: IEEE Computer Society Press. ISBN: 978-1-4799-1488-3.
doi:10.1109/CEC.2014.6900292 / pdf / slides
Indexing: EI:201446182716, WOS:000356684602065Mingxu Wan, Thomas Weise, and Ke Tang. Novel Loop Structures and the Evolution of Mathematical Algorithms. In Sara Silva, James A. Foster, Miguel Nicolau, Penousal Machado, and Mario Giacobini, editors, Proceedings of the 14th European Conference on Genetic Programming (EuroGP'11), volume 6621/2011 of Lecture Notes in Computer Science (LNCS), pages 49-60, April 27–29, 2011, Torino, Italy. ISBN: 978-3-642-20406-7, Berlin, Germany: Springer-Verlag GmbH.
doi:10.1007/978-3-642-20407-4_5 / pdf
Indexing: EI:20111913976760, WOS:000301802700005Thomas Weise and Michael Zapf. Evolving Distributed Algorithms with Genetic Programming: Election. In Lihong Xu, Erik D. Goodman, and Yongsheng Ding, editors, Proceedings of the First ACM/SIGEVO Summit on Genetic and Evolutionary Computation (GEC'09), pages 577-584, Shanghai, China: Hua-Ting Hotel & Towers, June 12–14, 2009. ISBN: 978-1-60558-326-6, New York, NY, USA: ACM Press.
doi:10.1145/1543834.1543913
Indexing: EI:20093012219539, WOS:000282382900079Thomas Weise, 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, Brijesh Verma, editor.
doi:10.1142/S1469026809002436
Indexing: EI:20092012083173, CCF-C类Michael Zapf and Thomas Weise. Applicability of Emergence Engineering to Distributed Systems Scenarios. Kasseler Informatikschriften (KIS) 2008, 5, Kassel, Hesse, Germany: University of Kassel, Fachbereich 16: Elektrotechnik/Informatik, January 9, 2009.
urn:nbn:de:hebis:34-2009010925609Michael Zapf and Thomas Weise. Can Solutions Emerge? Proceedings of the Third International Workshop on Self-Organizing Systems (IWSOS'08). Karin Anna Hummel and James P. G. Sterbenz, editors. December 10-12, 2008, Vienna, Austria. Volume 5343/2008 of Lecture Notes in Computer Science (LNCS), pages 299–304. ISBN 978-3-540-92156-1, Berlin, Germany: Springer-Verlag GmbH.
doi:10.1007/978-3-540-92157-8_29
Indexing: EI:20090411875952, WOS:000263515100029Thomas Weise, Michael Zapf, and Kurt Geihs. Evolving Proactive Aggregation Protocols. In Michael O'Neill, Leonardo Vanneschi, Steven Matt Gustafson, Anna Isabel Esparcia-Alcázar, Ivanoe de Falco, Antonio Della Cioppa, and Ernesto Tarantino, editors, Genetic Programming – Proceedings of the 11th European Conference on Genetic Programming (EuroGP'08), volume 4971/2008 of Lecture Notes in Computer Science (LNCS), pages 254-265, Naples, Italy, March 26–28, 2008. ISBN: 978-3-540-78670-2, Berlin, Germany: Springer-Verlag GmbH.
doi:10.1007/978-3-540-78671-9_22
Indexing: EI:20083011392084, WOS:000254506700022Thomas Weise, Michael Zapf, and Kurt Geihs. Rule-based Genetic Programming. In Proceedings of the 2nd International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS'07), pages 8-15, Budapest, Hungary: Radisson SAS Beke Hotel, December 10–12, 2007. ISBN: 978-963-9799-05-9, Piscataway, NJ, USA: IEEE Computer Society.
doi:10.1109/BIMNICS.2007.4610073
Indexing: EI:20084111632894, WOS:000268585800002, Google ScholarMichael Zapf and Thomas Weise. Offline Emergence Engineering For Agent Societies. Kasseler Informatikschriften (KIS) 2007, 8, Kassel, Hesse, Germany: University of Kassel, Fachbereich 16: Elektrotechnik/Informatik, December 7, 2007.
urn:nbn:de:hebis:34-2007120719844Thomas Weise, Michael Zapf, Mohammad Ullah Khan, and Kurt Geihs. Genetic Programming meets Model-Driven Development. In Andreas König, Mario Köppen, Ajith Abraham, Christian Igel, and Nikola Kasabov, editors, Proceedings of the 7th International Conference on Hybrid Intelligent Systems (HIS'07), pages 332-335, Kaiserslautern, Germany: Fraunhofer Center FhG ITWM/FhG IESE, September 17–19, 2007. Piscataway, NJ, USA: IEEE Computer Society.
doi:10.1109/HIS.2007.11
Indexing: EI:20082911386590Thomas Weise, Michael Zapf, Mohammad Ullah Khan, and Kurt Geihs. Genetic Programming meets Model-Driven Development. Kasseler Informatikschriften (KIS) 2007, 2, Kassel, Hesse, Germany: University of Kassel, Fachbereich 16: Elektrotechnik/Informatik, July 2, 2007.
urn:nbn:de:hebis:34-2007070218786Thomas Weise, Kurt Geihs, and Philipp Andreas Baer. Genetic Programming for Proactive Aggregation Protocols. In Bartłomiej Beliczyński, Andrzej Dzieliński, Marcin Iwanowski, and Bernardete Ribeiro, editors, Proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA'07), Part I, volume 4431/2007 of Lecture Notes in Computer Science (LNCS), pages 167-173, Warsaw, Poland: Warsaw University of Technology, April 11–17, 2007. ISBN: 978-3-540-71589-4, Berlin, Germany: Springer-Verlag GmbH.
doi:10.1007/978-3-540-71618-1_19
Indexing: EI:20080311022959, WOS:000246097200019Thomas Weise and Kurt Geihs. DGPF – An Adaptable Framework for Distributed Multi-Objective Search Algorithms Applied to the Genetic Programming of Sensor Networks. In Bogdan Filipič and Jurij Šilc, editors, Proceedings of the Second International Conference on Bioinspired Optimization Methods and their Applications (BIOMA'06), pages 157-166, Informacijska Družba (Information Society) / Ljubljana, Slovenia: Jožef Stefan International Postgraduate School, October 9–10, 2006. Ljubljana, Slovenia: Jožef Stefan Institute. ISBN: 9616303813, 9789616303811
proceedings
Indexing: EI:20124015482490, Google ScholarThomas Weise and Kurt Geihs. Genetic Programming Techniques for Sensor Networks. In Pedro José Marrón, editor, Tagungsband des 5. GI/ITG KuVS Fachgespräch “Drahtlose Sensornetze”, Stuttgart, Germany: Universität Stuttgart, Fakultät 5: Informatik, Elektrotechnik und Informationstechnik, Institut für Parallele und Verteilte Systeme (IPVS), July 17–18, 2006, pages 21-25. Proceedings published as Technical Report TR-2006-07 of Stuttgart, Germany: University of Stuttgart, Computer Science Faculty.
proceedings
Awards
Thomas Weise. 2010 Dissertation Thesis Award of the Association of German Engineers (Verein Deutscher Ingenieure, VDI) Nordhessen for the PhD dissertation, awarded in 2011