Swarm intelligence (SI) is an emerging field of artificial intelligence that takes inspiration in the collective and social behaviour of different groups of simple agents. The automatic evolution of programs is an active research area that has attracted a lot of interest and has been promoted mainly by the genetic programming paradigm. The main objective is to find computer programs from a high-level problem statement of what needs to be done, without needing to know the structure of the solution beforehand.

This webpage looks at the intersection between SI and automatic programming, providing a bibliography on the state-of-the-art of the automatic programming algorithms which use an SI metaheuristic as the search technique. The expression of swarm programming (SP) has been coined to cover all swarm-based automatic programming proposals.

2014

  • [DOI] A. V. Husselmann and K. A. Hawick, “Geometric Firefly Algorithms on Graphical Processing Units,” in Cuckoo Search and Firefly Algorithm, X. Yang, Ed., Springer, 2014, vol. 516, pp. 245-269.
    [Bibtex]
    @INCOLLECTION{Husselmann_2014,
      author = {Husselmann, A.V. and Hawick, K.A.},
      title = {Geometric Firefly Algorithms on Graphical Processing Units},
      booktitle = {Cuckoo Search and Firefly Algorithm},
      publisher = {Springer},
      year = {2014},
      editor = {Yang, Xin-She},
      volume = {516},
      series = {Studies in Computational Intelligence},
      pages = {245-269},
      doi = {10.1007/978-3-319-02141-6\_12},
      isbn = {978-3-319-02140-9},
      keywords = {CUDA; Visualisation; Combinatorial optimisation; GPU; Geometric},
      language = {English},
      owner = {jlolmo},
      timestamp = {2013.11.18}
    }
  • J. L. Olmo, B. Strack, J. P. DeShazo, S. Ventura, J. N. Clore, and K. J. Cios, “Assessing the quality of a large data set collected at 130 U.S. hospitals for data mining: The diabetes case study,” International Journal of Medical Informatics, vol. X, pp. 1-14, 2014.
    [Bibtex]
    @ARTICLE{Olmo_2014ijmi,
      author = {Olmo, J. L. and Strack, B. and DeShazo, J. P. and Ventura, S. and
      Clore, J. N. and Cios, K. J.},
      title = {Assessing the quality of a large data set collected at 130 U.S. hospitals
      for data mining: The diabetes case study},
      journal = {International Journal of Medical Informatics},
      year = {2014},
      volume = {X},
      pages = {1-14},
      owner = {jlolmo},
      timestamp = {2013.07.30}
    }
  • J. L. Olmo, J. R. Romero, and S. Ventura, “Swarm-based metaheuristics in automatic programming: a survey,” WIREs Data Mining and Knowledge Discovery, pp. 1-25, 2014.
    [Bibtex]
    @ARTICLE{Olmo_2014wires,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {Swarm-based metaheuristics in automatic programming: a survey},
      journal = {WIREs Data Mining and Knowledge Discovery},
      year = {2014},
      pages = {1-25},
      owner = {jlolmo},
      timestamp = {2014.10.21}
    }
  • [DOI] J. L. Olmo, J. R. Romero, and S. Ventura, “Single and multi-objective ant programming for mining interesting rare association rules,” International Journal of Hybrid Intelligent Systems (In Press), pp. 1-12, 2014.
    [Bibtex]
    @ARTICLE{Olmo_2014ijhis,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {Single and multi-objective ant programming for mining interesting
      rare association rules},
      journal = {International Journal of Hybrid Intelligent Systems (In Press)},
      year = {2014},
      pages = {1-12},
      doi = {10.3233/HIS-140195},
      owner = {jlolmo},
      timestamp = {2014.06.20}
    }
  • [DOI] J. L. Olmo, J. R. Romero, and S. Ventura, “Ant programming algorithms for classification,” in Biologically-Inspired Techniques for Knowledge Discovery and Data Mining, S. Alam, Ed., IGI Global, 2014.
    [Bibtex]
    @INCOLLECTION{Olmo_2014IGI,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {Ant programming algorithms for classification},
      booktitle = {Biologically-Inspired Techniques for Knowledge Discovery and Data
      Mining},
      publisher = {IGI Global},
      year = {2014},
      editor = {Shafiq Alam},
      doi = {10.4018/978-1-4666-6078-6},
      owner = {jlolmo},
      timestamp = {2014.06.05}
    }
  • [DOI] T. Si, A. De, and A. Bhattacharjee, “Grammatical Swarm Based-Adaptable Velocity Update Equations in Particle Swarm Optimizer,” in Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013, S. C. Satapathy, S. K. Udgata, and B. N. Biswal, Eds., Springer, 2014, vol. 247, pp. 197-206.
    [Bibtex]
    @INCOLLECTION{Si_2014,
      author = {Si, Tapas and De, Arunava and Bhattacharjee, AnupKumar},
      title = {Grammatical Swarm Based-Adaptable Velocity Update Equations in Particle
      Swarm Optimizer},
      booktitle = {Proceedings of the International Conference on Frontiers of Intelligent
      Computing: Theory and Applications (FICTA) 2013},
      publisher = {Springer},
      year = {2014},
      editor = {Satapathy, Suresh Chandra and Udgata, Siba K and Biswal, Bhabendra
      Narayan},
      volume = {247},
      series = {Advances in Intelligent Systems and Computing},
      pages = {197-206},
      doi = {10.1007/978-3-319-02931-3\_24},
      isbn = {978-3-319-02930-6},
      keywords = {Particle Swarm Optimizer; Genetic Programming; Grammatical Evolution;
      Grammatical Swarm; Comprehensive Learning Particle Swarm Optimizer;
      Velocity update equations; Optimization},
      owner = {jlolmo},
      timestamp = {2014.06.04}
    }
  • [DOI] M. A. Sotelo-Figueroa, H. J. Puga Soberanes, J. Martin-Carpio, H. J. Fraire-Huacuja, L. Cruz-Reyes, and J. A. Soria-Alcaraz, “Improving the Bin Packing Heuristic through Grammatical Evolution Based on Swarm Intelligence,” Mathematical Problems in Engineering, vol. 2014, p. 12, 2014.
    [Bibtex]
    @ARTICLE{Sotelo_2014,
      author = {Sotelo-Figueroa, M.A. and Puga Soberanes, H.J. and Martin-Carpio,
      J. and Fraire-Huacuja, H.J. and Cruz-Reyes, L. and Soria-Alcaraz,
      J.A.},
      title = {Improving the Bin Packing Heuristic through Grammatical Evolution
      Based on Swarm Intelligence},
      journal = {Mathematical Problems in Engineering},
      year = {2014},
      volume = {2014},
      pages = {12},
      doi = {10.1155/2014/545191},
      owner = {jlolmo},
      timestamp = {2014.10.21}
    }

2013

  • [DOI] A. Cano, J. L. Olmo, and S. Ventura, “Parallel multi-objective Ant Programming for classification using GPUs,” Journal of Parallel and Distributed Computing, vol. 73, iss. 6, pp. 713-728, 2013.
    [Bibtex]
    @ARTICLE{Cano_2013,
      author = {Alberto Cano and Juan Luis Olmo and Sebastián Ventura},
      title = {Parallel multi-objective Ant Programming for classification using
      {GPU}s},
      journal = {Journal of Parallel and Distributed Computing},
      year = {2013},
      volume = {73},
      pages = {713 - 728},
      number = {6},
      doi = {10.1016/j.jpdc.2013.01.017},
      issn = {0743-7315},
      keywords = {Ant programming (AP)},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] A. Hara, J. -I. Kushida, S. Tanabe, and T. Takahama, “Parallel Ant Programming using genetic operators,” in Computational Intelligence Applications (IWCIA), IEEE International Workshop on, 2013, pp. 75-80.
    [Bibtex]
    @INPROCEEDINGS{Hara_2013,
      author = {Hara, A. and Kushida, J.-I. and Tanabe, S. and Takahama, T.},
      title = {Parallel Ant Programming using genetic operators},
      booktitle = {Computational Intelligence Applications (IWCIA), IEEE International
      Workshop on},
      year = {2013},
      pages = {75-80},
      doi = {10.1109/IWCIA.2013.6624788},
      issn = {1883-3977},
      keywords = {ant colony optimisation;genetic algorithms;parallel programming;regression
      analysis;trees (mathematics);GP;ant colony optimization;ants pheromone
      communications;crossover operator;genetic operators;genetic programming;logical
      function synthesis;mutation operator;parallel ant programming;pheromone
      tables;search mechanism;selection operator;single prototype tree;symbolic
      regressions;tree-structural representations;Automatic programming;Equations;Genetics;Mathematical
      model;Prototypes;Regression tree analysis;Ant Colony Optimization;Genetic
      programming;Swarm Intelligence},
      owner = {jlolmo},
      timestamp = {2014.01.20}
    }
  • [DOI] C. Headleand and W. J. Teahan, “Grammatical Herding,” Journal of Computer Science Systems Biology, vol. 6, iss. 2, pp. 43-47, 2013.
    [Bibtex]
    @ARTICLE{Headleand_2013,
      author = {Headleand, C. and Teahan, W.J.},
      title = {Grammatical Herding},
      journal = {Journal of Computer Science Systems Biology},
      year = {2013},
      volume = {6},
      pages = {43-47},
      number = {2},
      doi = {10.4172/jcsb.1000099},
      owner = {jlolmo},
      timestamp = {2013.07.26}
    }
  • [DOI] C. Headleand, “Swarm Based Population Seeding of Grammatical Evolution,” Journal of Computer Science Systems Biology, vol. 6, pp. 132-135, 2013.
    [Bibtex]
    @ARTICLE{Headleand_2013b,
      author = {Headleand, C.},
      title = {Swarm Based Population Seeding of Grammatical Evolution},
      journal = {Journal of Computer Science Systems Biology},
      year = {2013},
      volume = {6},
      pages = {132-135},
      doi = {10.4172/jcsb.1000110},
      owner = {jlolmo},
      timestamp = {2013.07.26}
    }
  • Q. Liu, T. Odaka, J. Kuroiwa, and H. Ogura, “Application of an artificial fish swarm algorithm in symbolic regression,” IEICE Transactions on Information and Systems, vol. E96-D, pp. 872-895, 2013.
    [Bibtex]
    @ARTICLE{Liu_2013,
      author = {Liu, Q. and Odaka, T. and Kuroiwa, J. and Ogura, H.},
      title = {Application of an artificial fish swarm algorithm in symbolic regression},
      journal = {IEICE Transactions on Information and Systems},
      year = {2013},
      volume = {E96-D},
      pages = {872-895},
      owner = {jlolmo},
      timestamp = {2013.07.26}
    }
  • [DOI] S. Luis and M. V. dos Santos, “On the Evolvability of a Hybrid Ant Colony-Cartesian Genetic Programming Methodology,” in EuroGP, 2013, pp. 109-120.
    [Bibtex]
    @INPROCEEDINGS{Luis_2013,
      author = {Sweeney Luis and Marcus Vinicius dos Santos},
      title = {On the Evolvability of a Hybrid Ant Colony-Cartesian Genetic Programming
      Methodology},
      booktitle = {EuroGP},
      year = {2013},
      pages = {109-120},
      bibsource = {DBLP, http://dblp.uni-trier.de},
      doi = {10.1007/978-3-642-37207-0\_10},
      ee = {http://dx.doi.org/10.1007/978-3-642-37207-0_10},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • J. L. Olmo, “Minería de datos mediante programación automática con colonias de hormigas,” PhD Thesis, 2013.
    [Bibtex]
    @PHDTHESIS{Olmo_2013thesis,
      author = {Olmo, J. L.},
      title = {Miner\'ia de datos mediante programaci\'on autom\'atica con colonias
      de hormigas},
      school = {University of Cordoba},
      year = {2013},
      month = {March},
      owner = {jlolmo},
      timestamp = {2013.07.31},
      url = {http://helvia.uco.es/xmlui/handle/10396/9498}
    }
  • [DOI] J. L. Olmo, J. R. Romero, and S. Ventura, “On the use of ant programming for mining rare association rules,” in Nature and Biologically Inspired Computing (NaBIC), 5th World Congress on, 2013, pp. 219-224.
    [Bibtex]
    @INPROCEEDINGS{Olmo_2013nabic,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {On the use of ant programming for mining rare association rules},
      booktitle = {Nature and Biologically Inspired Computing (NaBIC), 5th World Congress
      on},
      year = {2013},
      pages = {219-224},
      doi = {10.1109/NaBIC.2013.6617866},
      issn = {2164-7143},
      keywords = {ant colony optimisation;context-free grammars;data mining;information
      retrieval;ant colony optimization;ant programming;association rule
      mining;context-free grammar;data extraction;multi-objective grammar;search
      space;Algorithm design and analysis;Association rules;Grammar;Machine
      learning algorithms;Measurement;Software algorithms;Association rule
      mining (ARM);ant colony optimization (ACO);ant programming (AP);data
      mining (DM)},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] J. L. Olmo, J. M. Luna, J. R. Romero, and S. Ventura, “Mining association rules with single and multi-objective grammar guided ant programming,” Integrated Computer-Aided Engineering, vol. 20, iss. 3, pp. 217-234, 2013.
    [Bibtex]
    @ARTICLE{Olmo_2013icae,
      author = {Olmo, J. L. and Luna, J. M. and Romero, J. R. and Ventura, S.},
      title = {Mining association rules with single and multi-objective grammar
      guided ant programming},
      journal = {Integrated Computer-Aided Engineering},
      year = {2013},
      volume = {20},
      pages = {217-234},
      number = {3},
      doi = {10.3233/ICA-130430},
      issn = {1083-4419},
      keywords = {Ant colony optimization (ACO) , ant programming (AP) , classification
      , data mining (DM) , grammar-based automatic programming},
      owner = {jlolmo},
      timestamp = {2011.09.22}
    }
  • [DOI] F. Qi, Y. Ma, X. Liu, and G. Ji, “A Hybrid Genetic Programming with Particle Swarm Optimization,” in Advances in Swarm Intelligence, Springer, 2013, vol. 7929, pp. 11-18.
    [Bibtex]
    @INCOLLECTION{Qi_2013,
      author = {Qi, Feng and Ma, Yinghong and Liu, Xiyu and Ji, Guangyong},
      title = {A Hybrid Genetic Programming with Particle Swarm Optimization},
      booktitle = {Advances in Swarm Intelligence},
      publisher = {Springer},
      year = {2013},
      volume = {7929},
      series = {LNCS},
      pages = {11-18},
      doi = {10.1007/978-3-642-38715-9\_2},
      isbn = {978-3-642-38714-2},
      keywords = {Genetic Programming; Particle Swarm Optimization; Evolving Rules;
      Symbolic Regression Problem},
      owner = {jlolmo},
      timestamp = {2013.08.15}
    }
  • [DOI] T. Si, A. De, and A. Bhattacharjee, “Grammatical Bee Colony,” in Swarm, Evolutionary, and Memetic Computing, B. Panigrahi, P. Suganthan, S. Das, and S. Dash, Eds., Springer, 2013, vol. 8297, pp. 436-445.
    [Bibtex]
    @INCOLLECTION{Si_2013,
      author = {Si, Tapas and De, Arunava and Bhattacharjee, AnupKumar},
      title = {Grammatical Bee Colony},
      booktitle = {Swarm, Evolutionary, and Memetic Computing},
      publisher = {Springer},
      year = {2013},
      editor = {Panigrahi, BijayaKetan and Suganthan, PonnuthuraiNagaratnam and Das,
      Swagatam and Dash, ShubhransuSekhar},
      volume = {8297},
      series = {LNCS},
      pages = {436-445},
      doi = {10.1007/978-3-319-03753-0\_39},
      isbn = {978-3-319-03752-3},
      keywords = {Artificial bee colony; Grammatical evolution; Grammatical bee colony;
      Grammatical differential evolution; Grammatical swarm},
      owner = {jlolmo},
      timestamp = {2014.06.04}
    }

2012

  • [DOI] D. Karaboga, C. Ozturk, N. Karaboga, and B. Gorkemli, “Artificial bee colony programming for symbolic regression ,” Information Sciences, vol. 209, pp. 1-15, 2012.
    [Bibtex]
    @ARTICLE{Karaboga_2012b,
      author = {Dervis Karaboga and Celal Ozturk and Nurhan Karaboga and Beyza Gorkemli},
      title = {Artificial bee colony programming for symbolic regression },
      journal = {Information Sciences},
      year = {2012},
      volume = {209},
      pages = {1 - 15},
      doi = {10.1016/j.ins.2012.05.002},
      issn = {0020-0255},
      keywords = {Genetic programming},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] N. Kumaresan, “Optimal control for stochastic singular integro-differential Takagi-Sugeno fuzzy system using ant colony programming,” Filomat, vol. 26, iss. 3, p. 415?426, 2012.
    [Bibtex]
    @ARTICLE{Kumaresan_2012,
      author = {Kumaresan, N.},
      title = {Optimal control for stochastic singular integro-differential Takagi-Sugeno
      fuzzy system using ant colony programming},
      journal = {Filomat},
      year = {2012},
      volume = {26},
      pages = {415?426},
      number = {3},
      doi = {10.2298/FIL1203415K},
      owner = {jlolmo},
      timestamp = {2013.07.30}
    }
  • [DOI] L. F. M. de López, N. G. Blas, and Alberto Arteta, “The optimal combination: Grammatical swarm, particle swarm optimization and neural networks,” Journal of Computational Science, vol. 3, iss. 1–2, pp. 46-55, 2012.
    [Bibtex]
    @ARTICLE{deMingo_2012,
      author = {Luis Fernando de Mingo L\'{o}pez and Nuria G\'{o}mez Blas and Alberto
      Arteta},
      title = {The optimal combination: Grammatical swarm, particle swarm optimization
      and neural networks},
      journal = {Journal of Computational Science},
      year = {2012},
      volume = {3},
      pages = {46 - 55},
      number = {1–2},
      abstract = {Social behaviour is mainly based on swarm colonies, in which each
      individual shares its knowledge about the environment with other
      individuals to get optimal solutions. Such co-operative model differs
      from competitive models in the way that individuals die and are born
      by combining information of alive ones. This paper presents the particle
      swarm optimization with differential evolution algorithm in order
      to train a neural network instead the classic back propagation algorithm.
      The performance of a neural network for particular problems is critically
      dependant on the choice of the processing elements, the net architecture
      and the learning algorithm. This work is focused in the development
      of methods for the evolutionary design of artificial neural networks.
      This paper focuses in optimizing the topology and structure of connectivity
      for these networks. },
      doi = {http://dx.doi.org/10.1016/j.jocs.2011.12.005},
      issn = {1877-7503},
      keywords = {Social intelligence},
      owner = {jlolmo},
      timestamp = {2014.06.04}
    }
  • [DOI] J. L. Olmo, J. R. Romero, and S. Ventura, “Classification rule mining using ant programming guided by grammar with multiple Pareto fronts,” Soft Computing, vol. 16, iss. 12, pp. 2143-2163, 2012.
    [Bibtex]
    @ARTICLE{Olmo_2012soco,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {Classification rule mining using ant programming guided by grammar
      with multiple {Pareto} fronts},
      journal = {Soft Computing},
      year = {2012},
      volume = {16},
      pages = {2143-2163},
      number = {12},
      doi = {10.1007/s00500-012-0883-8},
      issn = {1432-7643},
      keywords = {Ant programming (AP); Grammar-based automatic programming; Multi-objective
      ant colony optimization (MOACO); Classification; Data mining (DM)},
      language = {English},
      owner = {jlolmo},
      publisher = {Springer-Verlag},
      timestamp = {2013.05.10}
    }
  • [DOI] J. L. Olmo, J. R. Romero, and S. Ventura, “Multi-Objective Ant Programming for Mining Classification Rules,” in Genetic Programming, A. Moraglio, S. Silva, K. Krawiec, P. Machado, and C. Cotta, Eds., Springer Berlin Heidelberg, 2012, vol. 7244, pp. 146-157.
    [Bibtex]
    @INCOLLECTION{Olmo_2012eurogp,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {Multi-Objective Ant Programming for Mining Classification Rules},
      booktitle = {Genetic Programming},
      publisher = {Springer Berlin Heidelberg},
      year = {2012},
      editor = {Moraglio, Alberto and Silva, Sara and Krawiec, Krzysztof and Machado,
      Penousal and Cotta, Carlos},
      volume = {7244},
      series = {LNCS},
      pages = {146-157},
      doi = {10.1007/978-3-642-29139-5\_13},
      isbn = {978-3-642-29138-8},
      keywords = {Data mining; Classification; Ant programming; Genetic programming;
      Multi-objective optimization},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] J. L. Olmo, A. Cano, J. R. Romero, and S. Ventura, “Binary and multiclass imbalanced classification using multi-objective ant programming,” in Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on, 2012, pp. 70-76.
    [Bibtex]
    @INPROCEEDINGS{Olmo_2012isda,
      author = {Olmo, J. L. and Cano, A. and Romero, J. R. and Ventura, S.},
      title = {Binary and multiclass imbalanced classification using multi-objective
      ant programming},
      booktitle = {Intelligent Systems Design and Applications (ISDA), 2012 12th International
      Conference on},
      year = {2012},
      pages = {70-76},
      doi = {10.1109/ISDA.2012.6416515},
      issn = {2164-7143},
      keywords = {ant colony optimisation;data mining;grammars;pattern classification;binary
      imbalanced classification;binary solutions;multiclass imbalanced
      classification;multiclass solutions;multiobjective ant programming;multiobjective
      grammar-based ant programming algorithm;real domain applications;skewed
      data distributions;Clustering algorithms;Grammar;Intelligent systems;Partitioning
      algorithms;Prediction algorithms;Programming;Training;Multiclass
      imbalanced classification;ant colony optimization (ACO);ant programming
      (AP);data mining (DM);data set shift;multi-objective optimization},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }

2011

  • [DOI] A. Hara, M. Watanabe, and T. Takahama, “Cartesian Ant Programming,” in Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on, 2011, pp. 3161-3166.
    [Bibtex]
    @INPROCEEDINGS{Hara_2011,
      author = {Hara, A. and Watanabe, M. and Takahama, T.},
      title = {Cartesian Ant Programming},
      booktitle = {Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference
      on},
      year = {2011},
      pages = {3161-3166},
      doi = {10.1109/ICSMC.2011.6084146},
      issn = {1062-922X},
      keywords = {ant colony optimisation;genetic algorithms;trees (mathematics);ant
      colony optimization;automatic programming;cartesian ant programming;classification
      problem;combinatorial optimization;compact program;evolutionary method;genetic
      programming;graph structural program;pheromone communication;symbolic
      regression;tree-structural program optimization;Ant colony optimization;Automatic
      programming;Cities and towns;Equations;Optimization;Spirals;Ant Colony
      Optimization;Cartesian Genetic Programming;Genetic Programming;Swarm
      Intelligence},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] N. Kumaresan, “Optimal control for stochastic linear quadratic singular periodic neuro Takagi-Sugeno (T-S) fuzzy system with singular cost using ant colony programming,” Applied Mathematical Modelling, vol. 35, iss. 8, pp. 3797-3808, 2011.
    [Bibtex]
    @ARTICLE{Kumaresan_2011,
      author = {N. Kumaresan},
      title = {Optimal control for stochastic linear quadratic singular periodic
      neuro Takagi-Sugeno ({T-S}) fuzzy system with singular cost using
      ant colony programming},
      journal = {Applied Mathematical Modelling},
      year = {2011},
      volume = {35},
      pages = {3797 - 3808},
      number = {8},
      doi = {10.1016/j.apm.2011.02.017},
      issn = {0307-904X},
      keywords = {Ant colony programming},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] J. L. Olmo, J. R. Romero, and S. Ventura, “Using Ant Programming Guided by Grammar for Building Rule-Based Classifiers,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 41, iss. 6, pp. 1585-1599, 2011.
    [Bibtex]
    @ARTICLE{Olmo_2011smc,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {Using Ant Programming Guided by Grammar for Building Rule-Based Classifiers},
      journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics},
      year = {2011},
      volume = {41},
      pages = {1585-1599},
      number = {6},
      doi = {10.1109/TSMCB.2011.2157681},
      issn = {1083-4419},
      keywords = {context-free grammars;data mining;optimisation;pattern classification;ant-based
      algorithm;classification algorithm;classification rules mining;context-free
      grammar;expert domain decision;grammar based ant programming;rule-based
      classifiers;Algorithm design and analysis;Ant colony optimization;Automatic
      programming;Classification algorithms;Data mining;Grammar;Ant colony
      optimization (ACO);ant programming (AP);classification;data mining
      (DM);grammar-based automatic programming},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] J. L. Olmo, J. M. Luna, J. R. Romero, and S. Ventura, “Association rule mining using a multi-objective grammar-based ant programming algorithm,” in Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on, 2011, pp. 971-977.
    [Bibtex]
    @INPROCEEDINGS{Olmo_2011isda,
      author = {Olmo, J. L. and Luna, J. M. and Romero, J. R. and Ventura, S.},
      title = {Association rule mining using a multi-objective grammar-based ant
      programming algorithm},
      booktitle = {Intelligent Systems Design and Applications (ISDA), 2011 11th International
      Conference on},
      year = {2011},
      pages = {971-977},
      doi = {10.1109/ISDA.2011.6121784},
      issn = {2164-7143},
      keywords = {ant colony optimisation;context-free grammars;data mining;information
      retrieval;ant colony optimization;ant programming;association rule
      mining;context-free grammar;data extraction;multi-objective grammar;search
      space;Algorithm design and analysis;Association rules;Grammar;Machine
      learning algorithms;Measurement;Software algorithms;Association rule
      mining (ARM);ant colony optimization (ACO);ant programming (AP);data
      mining (DM)},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] S. Shirakawa, S. Ogino, and T. Nagao, “Automatic Construction of Programs Using Dynamic Ant Programming,” in Ant colony optimization methods and applications, A. Ostfeld, Ed., InTech, 2011, p. 75.
    [Bibtex]
    @INCOLLECTION{Shirakawa_2011,
      author = {Shirakawa, Shinichi and Ogino, Shintaro and Nagao, Tomoharu},
      title = {Automatic Construction of Programs Using Dynamic Ant Programming},
      booktitle = {Ant colony optimization methods and applications},
      publisher = {InTech},
      year = {2011},
      editor = {Avi Ostfeld},
      pages = {75},
      doi = {10.5772/13786},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }

2010

  • M. Boryczka, “Ant Colony Programming,” in Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications, R. Chiong, Ed., IGI Global, 2010, pp. 248-272.
    [Bibtex]
    @INCOLLECTION{Boryczka_2010,
      author = {Mariusz Boryczka},
      title = {Ant Colony Programming},
      booktitle = {Intelligent Systems for Automated Learning and Adaptation: Emerging
      Trends and Applications},
      publisher = {IGI Global},
      year = {2010},
      editor = {Raymond Chiong},
      pages = {248-272},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] N. Kumaresan and P. Balasubramaniam, “Singular optimal control for stochastic linear quadratic singular system using ant colony programming,” International Journal of Computer Mathematics, vol. 87, iss. 14, pp. 3311-3327, 2010.
    [Bibtex]
    @ARTICLE{Kumaresan_2010b,
      author = {N. Kumaresan and P. Balasubramaniam},
      title = {Singular optimal control for stochastic linear quadratic singular
      system using ant colony programming},
      journal = {International Journal of Computer Mathematics},
      year = {2010},
      volume = {87},
      pages = {3311-3327},
      number = {14},
      doi = {10.1080/00207160903026634},
      owner = {jlolmo},
      timestamp = {2013.07.30}
    }
  • N. Kumaresan, “Optimal control for stochastic linear quadratic singular Takagi-Sugeno fuzzy system using ant colony programming,” Neural, Parallel & Scientific Computations, vol. 18, iss. 1, pp. 89-108, 2010.
    [Bibtex]
    @ARTICLE{Kumaresan_2010a,
      author = {Kumaresan, N.},
      title = {Optimal control for stochastic linear quadratic singular Takagi-Sugeno
      fuzzy system using ant colony programming},
      journal = {Neural, Parallel \& Scientific Computations},
      year = {2010},
      volume = {18},
      pages = {89--108},
      number = {1},
      acmid = {1991923},
      address = {Atlanta, GA, USA},
      issn = {1061-5369},
      issue_date = {March 2010},
      keywords = {Runge Kutta method and stochastic linear quadratic singular Takagi
      Sugeno fuzzy system, ant colony programming, differential algebraic
      equation, matrix riccati differential equation, optimal control},
      numpages = {20},
      owner = {jlolmo},
      publisher = {Dynamic Publishers, Inc.},
      timestamp = {2013.07.30}
    }
  • [DOI] J. L. Olmo, J. R. Romero, and S. Ventura, “A grammar based Ant Programming algorithm for mining classification rules,” in Evolutionary Computation (CEC), 2010 IEEE Congress on, 2010, pp. 1-8.
    [Bibtex]
    @INPROCEEDINGS{Olmo_2010cec,
      author = {Olmo, J. L. and Romero, J. R. and Ventura, S.},
      title = {A grammar based Ant Programming algorithm for mining classification
      rules},
      booktitle = {Evolutionary Computation (CEC), 2010 IEEE Congress on},
      year = {2010},
      pages = {1-8},
      doi = {10.1109/CEC.2010.5586492},
      keywords = {context-free grammars;data mining;pattern classification;ACO-based
      automatic programming algorithm;context-free grammar;data mining;grammar
      based ant programming algorithm;mining classification rules;Automatic
      programming;Data mining;Grammar;Prediction algorithms;Production;Training},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] J. L. Olmo, J. M. Luna, J. R. Romero, and S. Ventura, “An Automatic Programming ACO-Based Algorithm for Classification Rule Mining,” in Trends in Practical Applications of Agents and Multiagent Systems, Y. D. et al., Ed., Springer, 2010, pp. 649-656.
    [Bibtex]
    @INCOLLECTION{Olmo_2010paams,
      author = {Olmo, J. L. and Luna, J. M. and Romero, J. R. and Ventura, S.},
      title = {An Automatic Programming ACO-Based Algorithm for Classification Rule
      Mining},
      booktitle = {Trends in Practical Applications of Agents and Multiagent Systems},
      publisher = {Springer},
      year = {2010},
      editor = {Yves Demazeau et al.},
      series = {LNAI},
      pages = {649--656},
      doi = {10.1007/978-3-642-12433-4\_76},
      owner = {jlolmo},
      timestamp = {2010.07.05}
    }

2009

  • [DOI] P. Kouchakpour, A. Zaknich, and T. Bräuni, “A survey and taxonomy of performance improvement of canonical genetic programming,” Knowledge and Information Systems, vol. 21, iss. 1, pp. 1-39, 2009.
    [Bibtex]
    @ARTICLE{Kouchakpour_2009,
      author = {Kouchakpour, Peyman and Zaknich, Anthony and Br\"{a}uni, Thomas},
      title = {A survey and taxonomy of performance improvement of canonical genetic
      programming},
      journal = {Knowledge and Information Systems},
      year = {2009},
      volume = {21},
      pages = {1--39},
      number = {1},
      month = oct,
      acmid = {1669194},
      address = {New York, NY, USA},
      doi = {10.1007/s10115-008-0184-9},
      issn = {0219-1377},
      issue_date = {October 2009},
      keywords = {Computational effort, Efficiency, Genetic programming, Performance
      improvement, Taxonomy},
      numpages = {39},
      owner = {jlolmo},
      publisher = {Springer-Verlag New York, Inc.},
      timestamp = {2013.07.30}
    }
  • [DOI] G. Ramstein, N. Beaume, and Y. Jacques, “Detection of Remote Protein Homologs Using Social Programming,” in Foundations of Computational Intelligence Volume 4, A. Abraham, A. Hassanien, and A. de Carvalho, Eds., Springer, 2009, vol. 204, pp. 277-296.
    [Bibtex]
    @INCOLLECTION{Ramstein_2009,
      author = {Ramstein, Gerard and Beaume, Nicolas and Jacques, Yannick},
      title = {Detection of Remote Protein Homologs Using Social Programming},
      booktitle = {Foundations of Computational Intelligence Volume 4},
      publisher = {Springer},
      year = {2009},
      editor = {Abraham, Ajith and Hassanien, Aboul-Ella and de Carvalho, AndréPoncedeLeonF.},
      volume = {204},
      series = {Studies in Computational Intelligence},
      pages = {277-296},
      doi = {10.1007/978-3-642-01088-0\_12},
      isbn = {978-3-642-01087-3},
      owner = {jlolmo},
      timestamp = {2014.06.10}
    }
  • A. Salehi-Abari and T. White, “The uphill battle of ant programming vs. genetic programming,” in International joint conference on computational intelligence (IJCCI), 2009, pp. 171-176.
    [Bibtex]
    @INPROCEEDINGS{Salehi_2009,
      author = {Salehi-Abari, Amirali and White, Tony},
      title = {The uphill battle of ant programming vs. genetic programming},
      booktitle = {International joint conference on computational intelligence (IJCCI)},
      year = {2009},
      pages = {171--176},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }

2008

  • [DOI] M. Boryczka, “Ant Colony Programming with the Candidate List,” in Agent and Multi-Agent Systems: Technologies and Applications, N. Nguyen, G. Jo, R. Howlett, and L. Jain, Eds., Springer Berlin Heidelberg, 2008, vol. 4953, pp. 302-311.
    [Bibtex]
    @INCOLLECTION{Boryczka_2008,
      author = {Boryczka, Mariusz},
      title = {Ant Colony Programming with the Candidate List},
      booktitle = {Agent and Multi-Agent Systems: Technologies and Applications},
      publisher = {Springer Berlin Heidelberg},
      year = {2008},
      editor = {Nguyen, NgocThanh and Jo, GeunSik and Howlett, RobertJ. and Jain,
      LakhmiC.},
      volume = {4953},
      series = {LNCS},
      pages = {302-311},
      doi = {10.1007/978-3-540-78582-8\_31},
      isbn = {978-3-540-78581-1},
      keywords = {ant colony system; symbolic regression; ant colony programming; candidate
      list},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] G. Ramstein, N. Beaume, and Y. Jacques, “A Grammatical Swarm for protein classification,” in Evolutionary Computation (CEC), 2008 IEEE Congress on, 2008, pp. 2561-2568.
    [Bibtex]
    @INPROCEEDINGS{Ramstein_2008,
      author = {Ramstein, G. and Beaume, N. and Jacques, Y.},
      title = {A Grammatical Swarm for protein classification},
      booktitle = {Evolutionary Computation (CEC), 2008 IEEE Congress on},
      year = {2008},
      pages = {2561-2568},
      doi = {10.1109/CEC.2008.4631142},
      keywords = {Bayes methods;biology computing;macromolecules;optimisation;pattern
      classification;proteins;support vector machines;Naive Bayes classifiers;aggregation
      operator;cytokines;fitness criterion;grammatical swarm;optimal ranking;protein
      classification;protein sequences;ranking quality;support vector machine;Application
      software;Bioinformatics;Data mining;Error analysis;Genetic algorithms;Genetic
      programming;Laboratories;Proteins;Support vector machine classification;Support
      vector machines},
      owner = {jlolmo},
      timestamp = {2014.06.04}
    }
  • [DOI] A. Salehi-Abari and T. White, “Enhanced generalized ant programming (EGAP),” in Genetic and Evolutionary Computation Conference (GECCO), 2008, pp. 111-118.
    [Bibtex]
    @INPROCEEDINGS{Salehi_2008,
      author = {Salehi-Abari, Amirali and White, Tony},
      title = {Enhanced generalized ant programming ({EGAP})},
      booktitle = {Genetic and Evolutionary Computation Conference (GECCO)},
      year = {2008},
      pages = {111--118},
      publisher = {ACM},
      acmid = {1389111},
      doi = {10.1145/1389095.1389111},
      isbn = {978-1-60558-130-9},
      keywords = {ant programming, automatic programming, enhanced generalized ant programming,
      generalized ant programming, heuristic},
      location = {Atlanta, GA, USA},
      numpages = {8},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • [DOI] S. Shirakawa, S. Ogino, and T. Nagao, “Dynamic ant programming for automatic construction of programs,” IEEJ Transactions on Electrical and Electronic Engineering, vol. 3, iss. 5, pp. 540-548, 2008.
    [Bibtex]
    @ARTICLE{Shirakawa_2008,
      author = {Shirakawa, Shinichi and Ogino, Shintaro and Nagao, Tomoharu},
      title = {Dynamic ant programming for automatic construction of programs},
      journal = {IEEJ Transactions on Electrical and Electronic Engineering},
      year = {2008},
      volume = {3},
      pages = {540--548},
      number = {5},
      doi = {10.1002/tee.20311},
      issn = {1931-4981},
      keywords = {ant colony optimization, swarm intelligence, genetic programming,
      automatic programming},
      owner = {jlolmo},
      publisher = {Wiley Subscription Services, Inc., A Wiley Company},
      timestamp = {2013.05.10}
    }
  • J. Togelius, R. D. Nardi, and A. Moraglio, “Geometric PSO + GP = Particle Swarm Programming,” in IEEE Congress on Evolutionary Computation, 2008, pp. 3594-3600.
    [Bibtex]
    @INPROCEEDINGS{Togelius_2008,
      author = {Julian Togelius and Renzo De Nardi and Alberto Moraglio},
      title = {Geometric {PSO + GP} = Particle Swarm Programming},
      booktitle = {IEEE Congress on Evolutionary Computation},
      year = {2008},
      pages = {3594-3600},
      bibsource = {DBLP, http://dblp.uni-trier.de},
      owner = {jlolmo},
      timestamp = {2013.08.09}
    }

2006

  • M. O`Neill, F. Leahy, and A. Brabazon, “Grammatical Swarm: A Variable-Length Particle Swarm Algorithm,” in Swarm Intelligent Systems, Springer, 2006, pp. 59-74.
    [Bibtex]
    @INCOLLECTION{ONeill_2006b,
      author = {Michael O`Neill and Finbar Leahy and Anthony Brabazon},
      title = {Grammatical Swarm: A Variable-Length Particle Swarm Algorithm},
      booktitle = {Swarm Intelligent Systems},
      publisher = {Springer},
      year = {2006},
      series = {Studies in Computational Intelligence},
      pages = {59-74},
      bibsource = {DBLP, http://dblp.uni-trier.de},
      owner = {jlolmo},
      timestamp = {2013.08.09}
    }
  • [DOI] M. O`Neill and A. Brabazon, “Grammatical Swarm: The generation of programs by social programming,” Natural Computing, vol. 5, iss. 4, pp. 443-462, 2006.
    [Bibtex]
    @ARTICLE{ONeill_2006,
      author = {O`Neill, Michael and Brabazon, Anthony},
      title = {Grammatical Swarm: The generation of programs by social programming},
      journal = {Natural Computing},
      year = {2006},
      volume = {5},
      pages = {443-462},
      number = {4},
      doi = {10.1007/s11047-006-9007-7},
      issn = {1567-7818},
      keywords = {genetic programming; grammatical evolution; particle swarm optimization;
      social learning; social programming},
      language = {English},
      owner = {jlolmo},
      publisher = {Kluwer Academic Publishers},
      timestamp = {2013.05.10}
    }

2005

  • M. Boryczka, “Eliminating Introns in Ant Colony Programming,” Fundamenta Informaticae, vol. 68, iss. 1-2, pp. 1-19, 2005.
    [Bibtex]
    @ARTICLE{Boryczka2005,
      author = {Boryczka, Mariusz},
      title = {Eliminating Introns in Ant Colony Programming},
      journal = {Fundamenta Informaticae},
      year = {2005},
      volume = {68},
      pages = {1--19},
      number = {1-2},
      address = {Amsterdam, The Netherlands, The Netherlands},
      issn = {0169-2968},
      owner = {Juan Luis},
      publisher = {IOS Press},
      timestamp = {2010.04.06}
    }
  • F. Leahy, “Social Programming: Investigations in Grammatical Swarm,” Master of Science in Software Engineering Master Thesis, University of Limerick, Ireland, 2005.
    [Bibtex]
    @MASTERSTHESIS{Leahy_2005,
      author = {Leahy, Finbar},
      title = {Social Programming: Investigations in Grammatical Swarm},
      school = {University of Limerick},
      year = {2005},
      type = {Master of Science in Software Engineering},
      address = {University of Limerick, Ireland},
      added-at = {2008-06-19T17:35:00.000+0200},
      biburl = {http://www.bibsonomy.org/bibtex/25bd5698a4cac956308925eb4443e5aed/brazovayeye},
      interhash = {a6e923e128fe75a273cdd5fef6070eaf},
      intrahash = {5bd5698a4cac956308925eb4443e5aed},
      keywords = {algorithms, evolution, genetic grammatical programming, swarm},
      language = {en},
      owner = {jlolmo},
      size = {129 pages},
      timestamp = {2008-06-19T17:35:00.000+0200}
    }
  • [DOI] C. Veenhuis, M. Koppen, J. Kruger, and B. Nickolay, “Tree swarm optimization: an approach to PSO-based tree discovery,” in Evolutionary Computation (CEC), 2005 IEEE Congress on, 2005, pp. 1238-1245.
    [Bibtex]
    @INPROCEEDINGS{Veenhuis_2005,
      author = {Veenhuis, C. and Koppen, M. and Kruger, J. and Nickolay, B.},
      title = {Tree swarm optimization: an approach to {PSO}-based tree discovery},
      booktitle = {Evolutionary Computation (CEC), 2005 IEEE Congress on},
      year = {2005},
      volume = {2},
      pages = {1238-1245},
      doi = {10.1109/CEC.2005.1554832},
      keywords = {learning (artificial intelligence);particle swarm optimisation;trees
      (mathematics);fitness function;function optimization;particle swarm
      optimization;swarm-based learning algorithm;tree discovery;tree spaces;tree
      swarm optimization;Ant colony optimization;Assembly;Birds;Classification
      tree analysis;Decision trees;Genetic programming;Machine learning;Machine
      learning algorithms;Optimization methods;Particle swarm optimization},
      owner = {jlolmo},
      timestamp = {2014.06.06}
    }

2004

  • [DOI] Y. Chen, J. Dong, and B. Yang, “Automatic Design of Hierarchical TS-FS Model Using Ant Programming and PSO Algorithm,” in Artificial Intelligence: Methodology, Systems, and Applications, C. Bussler and D. Fensel, Eds., Springer, 2004, vol. 3192, pp. 285-294.
    [Bibtex]
    @INCOLLECTION{Chen_2004b,
      author = {Chen, Yuehui and Dong, Jiwen and Yang, Bo},
      title = {Automatic Design of Hierarchical TS-FS Model Using Ant Programming
      and PSO Algorithm},
      booktitle = {Artificial Intelligence: Methodology, Systems, and Applications},
      publisher = {Springer},
      year = {2004},
      editor = {Bussler, Christoph and Fensel, Dieter},
      volume = {3192},
      series = {LNCS},
      pages = {285-294},
      doi = {10.1007/978-3-540-30106-6\_29},
      isbn = {978-3-540-22959-9},
      owner = {jlolmo},
      timestamp = {2014.06.01}
    }
  • [DOI] Y. Chen, B. Yang, and J. Dong, “Evolving Flexible Neural Networks Using Ant Programming and PSO Algorithms,” in Advances in Neural Networks, 2004.
    [Bibtex]
    @INPROCEEDINGS{Chen_2004,
      author = {Yuehui Chen and Bo Yang and Jiwen Dong},
      title = {Evolving Flexible Neural Networks Using Ant Programming and {PSO}
      Algorithms},
      booktitle = {Advances in Neural Networks},
      year = {2004},
      volume = {3173},
      series = {LNCS},
      bibsource = {DBLP, http://dblp.uni-trier.de},
      chapter = {Evolving Flexible Neural Networks Using Ant Programming and {PSO}
      Algorithms},
      doi = {10.1007/978-3-540-28647-9\_36},
      ee = {http://springerlink.metapress.com/openurl.asp?genre=article{\&}issn=0302-9743{\&}volume=3173{\&}spage=211},
      owner = {jlolmo},
      timestamp = {2010.06.21}
    }
  • J. Green, J. Whalley, C. G. Johnson, and others, “Automatic programming with ant colony optimization,” in UK Workshop on Computational Intelligence, 2004, pp. 70-77.
    [Bibtex]
    @INPROCEEDINGS{Green_2004,
      author = {Green, Jennifer and Whalley, Jacqueline and Johnson, Colin G and
      others},
      title = {Automatic programming with ant colony optimization},
      booktitle = {UK Workshop on Computational Intelligence},
      year = {2004},
      pages = {70--77},
      organization = {Loughborough University},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • C. Keber and M. G. Schuster, “Collective intelligence in option pricing: determining black-scholfs implied volatilities with generalized ant programming,” in World Automation Congress, 2004, pp. 465-470.
    [Bibtex]
    @INPROCEEDINGS{Keber_2004,
      author = {Keber, C. and Schuster, M.G.},
      title = {Collective intelligence in option pricing: determining black-scholfs
      implied volatilities with generalized ant programming},
      booktitle = {World Automation Congress},
      year = {2004},
      volume = {17},
      pages = {465-470},
      month = {June},
      keywords = {Approximation methods;Closed-form solution;Cost accounting;Distribution
      functions;Genetic programming;Newton method;Pricing;Ant Programming;Collective
      Intelligence;Nature-Based Heuristics;Option Pricing;Symbolic Regression},
      owner = {jlolmo},
      timestamp = {2014.06.01}
    }
  • M. O`Neill and A. Brabazon, “Grammatical Swarm,” in Genetic and Evolutionary Computation Conference (GECCO), 2004, pp. 163-174.
    [Bibtex]
    @INPROCEEDINGS{ONeill_2004a,
      author = {Michael O`Neill and Anthony Brabazon},
      title = {Grammatical Swarm},
      booktitle = {Genetic and Evolutionary Computation Conference (GECCO)},
      year = {2004},
      pages = {163-174},
      bibsource = {DBLP, http://dblp.uni-trier.de},
      owner = {jlolmo},
      timestamp = {2013.08.09}
    }
  • [DOI] M. O`Neill, A. Brabazon, and C. Adley, “The automatic generation of programs for classification problems with grammatical swarm,” in Evolutionary Computation, 2004. CEC2004. Congress on, 2004, p. 104-110 Vol.1.
    [Bibtex]
    @INPROCEEDINGS{ONeill_2004b,
      author = {O`Neill, M. and Brabazon, A. and Adley, C.},
      title = {The automatic generation of programs for classification problems
      with grammatical swarm},
      booktitle = {Evolutionary Computation, 2004. CEC2004. Congress on},
      year = {2004},
      volume = {1},
      pages = {104-110 Vol.1},
      doi = {10.1109/CEC.2004.1330844},
      keywords = {automatic programming;evolutionary computation;grammars;optimisation;DNA
      promoter sequences;automatic program generation;bioinformatics problem;classification
      problems;evolutionary automatic programming;grammatical evolution;grammatical
      swarm;mushroom classification problem;particle swarm algorithm;program
      construction rules;Automatic programming;Birds;Control systems;DNA;Educational
      institutions;Insects;Marine animals;Particle swarm optimization;Robustness;Sequences},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • S. A. Rojas and P. J. Bentley, “A grid-based ant colony system for automatic program synthesis,” in Genetic and Evolutionary Computation Conference (GECCO), 2004, pp. 1-12.
    [Bibtex]
    @INPROCEEDINGS{Rojas_2004,
      author = {Sergio A. Rojas and Peter. J. Bentley},
      title = {A grid-based ant colony system for automatic program synthesis},
      booktitle = {Genetic and Evolutionary Computation Conference (GECCO)},
      year = {2004},
      editor = {R. Poli et al.},
      series = {Late Braking Papers},
      pages = {1--12},
      abstract = {We present a work in progress describing attribute grammar approaches
      to Grammatical Evolution, which allow us to encode context-sensitive
      and semantic information. Performance of the different grammars adopted
      are directly compared with a more traditional GA representation on
      five instances of an NP-hard knapsack problem. The results presented
      are encouraging, demonstrating that Grammatical Evolution in conjunction
      with alternative grammar representations can provide an improvement
      over the standard context-free grammar, and allow Grammatical Evolution
      to drive a constraint based search.},
      keywords = {genetic algorithms, genetic programming, grammatical evolution},
      notes = {attributes (information, integers or list) can be assigned to any
      symbol of the (recursive) grammar and are defined (given meaning)
      by functions associated with the grammar's productions. Attribute
      values from child nodes (synthesised) or from parent nodes (inherited).
      Information (constants) starts from root (eg maxim weight) or leafs
      (weight of individual items). Conditions (eg if(notinknapsack) and
      if(usage+item < limit) ) are added to grammar productions plus functions
      to calculate them (eg limit=limit, usage=usage). Figure 1, page 8.
      pop=50, gens<=2000.
      
       Cited by \cite{Ortega:2007:ieeeTEC}. GECCO-2004WKS Distributed on
      CD-ROM at GECCO-2004},
      owner = {Juan Luis},
      timestamp = {2010.04.05}
    }

2003

  • M. Boryczka, Z. J. Czech, and W. Wieczorek, “Ant Colony Programming for Approximation Problems,” in Genetic and Evolutionary Computation Conference (GECCO), 2003, pp. 142-143.
    [Bibtex]
    @INPROCEEDINGS{Boryczka_2003,
      author = {Mariusz Boryczka and Zbigniew J. Czech and Wojciech Wieczorek},
      title = {Ant Colony Programming for Approximation Problems},
      booktitle = {Genetic and Evolutionary Computation Conference (GECCO)},
      year = {2003},
      pages = {142-143},
      bibsource = {DBLP, http://dblp.uni-trier.de},
      ee = {http://link.springer.de/link/service/series/0558/bibs/2723/27230142.htm},
      owner = {Juan Luis},
      timestamp = {2010.04.06}
    }
  • [DOI] C. Keber and M. G. Schuster, “Generalized ant programming in option pricing: determining implied volatilities based on American put options,” in Computational Intelligence for Financial Engineering (IEEE CIFER), Proceedings of the IEEE International Conference on, 2003, pp. 123-130.
    [Bibtex]
    @INPROCEEDINGS{Keber_2003,
      author = {Keber, C. and Schuster, M.G.},
      title = {Generalized ant programming in option pricing: determining implied
      volatilities based on American put options},
      booktitle = {Computational Intelligence for Financial Engineering (IEEE CIFER),
      Proceedings of the IEEE International Conference on},
      year = {2003},
      pages = {123-130},
      doi = {10.1109/CIFER.2003.1196251},
      keywords = {artificial life;costing;financial data processing;genetic algorithms;stock
      markets;American put options;generalized ant programming;genetic
      programming;heuristics;implied volatilities;option pricing;validation
      data sets;Ant colony optimization;Biological neural networks;Brain
      modeling;Closed-form solution;Cost accounting;Genetic programming;Heuristic
      algorithms;Lattices;Pricing;Problem-solving},
      owner = {jlolmo},
      timestamp = {2013.07.30}
    }
  • M. O`Neill and C. Ryan, Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language, Kluwer Academic Publishers, 2003.
    [Bibtex]
    @BOOK{ONeill_2003,
      title = {Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary
      Language},
      publisher = {Kluwer Academic Publishers},
      year = {2003},
      author = {O`Neill, Michael and Ryan, Conor},
      isbn = {1402074441},
      owner = {jlolmo},
      timestamp = {2013.08.16}
    }

2002

  • [DOI] H. A. Abbass, X. Hoai, and R. I. Mckay, “AntTAG: A New Method to Compose Computer Programs Using Colonies of Ants,” in IEEE Congress on Evolutionary Computation (IEEE CEC), 2002, pp. 1654-1659.
    [Bibtex]
    @INPROCEEDINGS{Abbass_2002,
      author = {Hussein A. Abbass and Xuan Hoai and Robert I. Mckay},
      title = {{AntTAG}: A New Method to Compose Computer Programs Using Colonies
      of Ants},
      booktitle = {IEEE Congress on Evolutionary Computation (IEEE CEC)},
      year = {2002},
      pages = {1654--1659},
      doi = {10.1109/CEC.2002.1004490},
      owner = {Juan Luis},
      timestamp = {2010.01.24}
    }
  • [DOI] M. Birattari, G. Caro, and M. Dorigo, “Toward the Formal Foundation of Ant Programming,” in Ant Algorithms, M. Dorigo, G. Caro, and M. Sampels, Eds., Springer Berlin Heidelberg, 2002, vol. 2463, pp. 188-201.
    [Bibtex]
    @INCOLLECTION{Birattari_2002,
      author = {Birattari, Mauro and Caro, Gianni and Dorigo, Marco},
      title = {Toward the Formal Foundation of Ant Programming},
      booktitle = {Ant Algorithms},
      publisher = {Springer Berlin Heidelberg},
      year = {2002},
      editor = {Dorigo, Marco and Caro, Gianni and Sampels, Michael},
      volume = {2463},
      series = {Lecture Notes in Computer Science},
      pages = {188-201},
      doi = {10.1007/3-540-45724-0_16},
      isbn = {978-3-540-44146-5},
      language = {English},
      owner = {jlolmo},
      timestamp = {2013.05.10}
    }
  • M. Boryczka and Z. J. Czech, “Solving Approximation Problems by Ant Colony Programming,” in Genetic and Evolutionary Computation Conference (GECCO), 2002, pp. 39-46.
    [Bibtex]
    @INPROCEEDINGS{Boryczka_2002,
      author = {Boryczka, Mariusz and Czech, Zbigniew J.},
      title = {Solving Approximation Problems by Ant Colony Programming},
      booktitle = {Genetic and Evolutionary Computation Conference (GECCO)},
      year = {2002},
      pages = {39--46},
      citeulike-article-id = {6583799},
      keywords = {ant-programming},
      owner = {Juan Luis},
      posted-at = {2010-01-24 15:29:31},
      priority = {2},
      timestamp = {2010.01.24}
    }
  • [DOI] M. Boryczka, “Ant Colony Programming for Approximation Problems,” in Intelligent Information Systems, Springer, 2002, vol. 17, pp. 147-156.
    [Bibtex]
    @INCOLLECTION{Boryczka_2002a,
      author = {Boryczka, Mariusz},
      title = {Ant Colony Programming for Approximation Problems},
      booktitle = {Intelligent Information Systems},
      publisher = {Springer},
      year = {2002},
      volume = {17},
      series = {Advances in Soft Computing},
      pages = {147-156},
      doi = {10.1007/978-3-7908-1777-5\_15},
      isbn = {978-3-7908-1509-2},
      keywords = {Automatic programming; genetic programming; ant colony programming;
      ant colony systems; approximation problems},
      language = {English},
      owner = {jlolmo},
      timestamp = {2014.06.01}
    }
  • C. Keber and M. G. Schuster, “Option Valuation With Generalized Ant Programming,” in Genetic and Evolutionary Computation Conference (GECCO), 2002, pp. 74-81.
    [Bibtex]
    @INPROCEEDINGS{Keber_2002,
      author = {Christian Keber and Matthias G. Schuster},
      title = {Option Valuation With Generalized Ant Programming},
      booktitle = {Genetic and Evolutionary Computation Conference (GECCO)},
      year = {2002},
      pages = {74--81},
      abstract = {For the valuation of American put options exact pricing formulas haven't
      as yet been derived We therefore determine analytical approximations
      for pricing such options by introducing the Generalised Ant Programming
      (GAP) approach applicable to all problems in which the search space
      of feasible solutions consists of computer programs. GAP is a new
      method inspired by Genetic Programming as well as by Ant Algorithms.
      Applying our GAP-approximations for the valuation of American put
      options on non-dividend paying stocks to experimental data as well
      as huge validation data sets we can show that our formulas deliver
      accurate results and outperform other formulas presented in the literature.},
      isbn = {1-55860-878-8},
      keywords = {genetic algorithms, genetic programming, artificial life, adaptive
      behavior, agents, ant colony optimization, ant algorithm, ant programming,
      option valuation, symbolic regression},
      notes = {GECCO-2002. A joint meeting of the eleventh International Conference
      on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic
      Programming Conference (GP-2002) },
      owner = {Juan Luis},
      publisher_address = {San Francisco, CA 94104, USA},
      timestamp = {2010.01.24}
    }
  • Y. Shan, H. Abbass, R. I. Mckay, and D. Essam, “AntTAG: a further study,” in Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems, 2002.
    [Bibtex]
    @INPROCEEDINGS{Shan_2002,
      author = {Y. Shan and H. Abbass and R. I. Mckay and D. Essam},
      title = {{AntTAG}: a further study},
      booktitle = {Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems},
      year = {2002},
      owner = {jlolmo},
      timestamp = {2013.07.30}
    }

2000

  • O. Roux and C. Fonlupt, “Ant Programming: or how to use ants for automatic programming,” in International conference on Swarm Intelligence (ANTS), 2000, pp. 121-129.
    [Bibtex]
    @INPROCEEDINGS{Roux_2000,
      author = {Roux, O. and Fonlupt, C.},
      title = {Ant Programming: or how to use ants for automatic programming},
      booktitle = {International conference on Swarm Intelligence (ANTS)},
      year = {2000},
      pages = {121--129},
      citeulike-article-id = {6304870},
      keywords = {ant-programming},
      owner = {jlolmo},
      posted-at = {2009-12-04 12:33:10},
      priority = {2},
      timestamp = {2012.06.05}
    }

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