Exploration of the effect of uncertainty in homogeneous and heterogeneous multi-agent societies with regard to their average characteristics

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@InProceedings{Georgiev:2018:GECCOcompa,
  author =       "Milen Georgiev and Ivan Tanev and 
                 Katsunori Shimohara",
  title =        "Exploration of the effect of uncertainty in
                 homogeneous and heterogeneous multi-agent societies
                 with regard to their average characteristics",
  booktitle =    "Workshop on Evolutionary Algorithms for Problems with
                 Uncertainty, GECCO '18: Proceedings of the Genetic and
                 Evolutionary Computation Conference Companion",
  year =         "2018",
  editor =       "Carlos Cotta and Tapabrata Ray and Hisao Ishibuchi and 
                 Shigeru Obayashi and Bogdan Filipic and 
                 Thomas Bartz-Beielstein and Grant Dick and 
                 Masaharu Munetomo and Silvino {Fernandez Alzueta} and Thomas Stuetzle and 
                 Pablo Valledor Pellicer and Manuel Lopez-Ibanez and 
                 Daniel R. Tauritz and Pietro S. Oliveto and 
                 Thomas Weise and Borys Wrobel and Ales Zamuda and 
                 Anne Auger and Julien Bect and Dimo Brockhoff and 
                 Nikolaus Hansen and Rodolphe {Le Riche} and Victor Picheny and 
                 Bilel Derbel and Ke Li and Hui Li and Xiaodong Li and 
                 Saul Zapotecas and Qingfu Zhang and Stephane Doncieux and 
                 Richard Duro and Joshua Auerbach and 
                 Harold {de Vladar} and Antonio J. Fernandez-Leiva and JJ Merelo and 
                 Pedro A. Castillo-Valdivieso and David Camacho-Fernandez and 
                 Francisco {Chavez de la O} and Ozgur Akman and 
                 Khulood Alyahya and Juergen Branke and Kevin Doherty and 
                 Jonathan Fieldsend and Giuseppe Carlo Marano and 
                 Nikos D. Lagaros and Koichi Nakayama and Chika Oshima and 
                 Stefan Wagner and Michael Affenzeller and 
                 Boris Naujoks and Vanessa Volz and Tea Tusar and Pascal Kerschke and 
                 Riyad Alshammari and Tokunbo Makanju and 
                 Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and 
                 John R. Woodward and Shin Yoo and John McCall and 
                 Nayat Sanchez-Pi and Luis Marti and Danilo Vasconcellos and 
                 Masaya Nakata and Anthony Stein and 
                 Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and 
                 Gabriela Ochoa and Stephen L. Smith and Stefano Cagnoni and 
                 Robert M. Patton and William {La Cava} and 
                 Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and 
                 Ivanoe {De Falco} and Antonio {Della Cioppa} and 
                 Ernesto Tarantino and Umberto Scafuri and P. G. M. Baltus and 
                 Giovanni Iacca and Ahmed Hallawa and Anil Yaman and 
                 Alma Rahat and Handing Wang and Yaochu Jin and 
                 David Walker and Richard Everson and Akira Oyama and 
                 Koji Shimoyama and Hemant Kumar and Kazuhisa Chiba and 
                 Pramudita Satria Palar",
  isbn13 =       "978-1-4503-5764-7",
  pages =        "1797--1804",
  address =      "Kyoto, Japan",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "15-19 " # jul,
  organisation = "SIGEVO",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1145/3205651.3208259",
  abstract =     "In electrical engineering, the deviation from average
                 values of a signal is viewed as noise to the useful
                 measurement. In human societies, however, the diversity
                 of the exhibited characteristics are a sign of
                 individuality and personal worth. We investigate the
                 effect of uncertainty variables in the environment on
                 multi-agent societies (MAS) and the consequences of the
                 deviation, from the average features of the modelled
                 agents. We show the performance of heterogeneous MAS of
                 agents in comparison to morphologically identical
                 homogeneous systems, preserving the same average
                 physical and sensory abilities for the system as a
                 whole, in a dynamic environment. We are employing a
                 form of the predator-prey pursuit problem in attempt to
                 measure the different performance of homogeneous MAS
                 with average parameters and its heterogeneous
                 counterpart. The effects of uncertainty in our work is
                 investigated from the viewpoint of (i) employing a
                 limited number of initial situations to evolve the team
                 of predator agents, (ii) generality to unforeseen
                 initial situations, and (iii) robustness to perception
                 noise. Key statistics are the efficiency of evolution
                 of the successful behaviour of predator agents,
                 effectiveness of their behaviour and its degradation
                 because of newly introduced situation or noise.
                 Preliminary results indicate that a heterogeneous
                 system can be at least as good as its homogeneous
                 average equivalent, in solution quality at the expense
                 of the runtime of evolution.",
  notes =        "Also known as \cite{3208259} GECCO-2018 A
                 Recombination of the 27th International Conference on
                 Genetic Algorithms (ICGA-2018) and the 23rd Annual
                 Genetic Programming Conference (GP-2018)",
}

Genetic Programming entries for Milen Georgiev Ivan T Tanev Katsunori Shimohara

Citations