Table of Contents

• SSNNS -: a suite of tools to explore spiking neural networksHeike Sichtig, J. David Schaffer, Craig B. Laramee. 1787-1790 [doi]
• Towards high speed multiobjective evolutionary optimizersA. K. M. Khaled Ahsan Talukder. 1791-1794 [doi]
• Multiple sequence alignment using a GLOCSA guided genetic algorithmEdgar David Arenas-Díaz, Helga Ochoterena-Booth, Katya Rodríguez-Vázquez. 1795-1798 [doi]
• Accelerating convergence using rough sets theory for multi-objective optimization problemsLuis V. Santana-Quintero, Carlos A. Coello Coello. 1799-1802 [doi]
• How social structure and institutional order co-evolve beyond instrumental rationalityJae-Woo Kim. 1803-1806 [doi]
• Specialization with NeuroEvolution in a collective behaviour taskD. W. F. van Krevelen. 1807-1810 [doi]
• Local dominance and controlling dominance area of solutions in multi and many objectives EAsHiroyuki Sato, Hernán E. Aguirre, Kiyoshi Tanaka. 1811-1814 [doi]
• Using holey fitness landscapes to counteract premature convergence in evolutionary algorithmsGreg Paperin. 1815-1818 [doi]
• Search-based test case generation for object-oriented java software using strongly-typed genetic programmingJosé Carlos Bregieiro Ribeiro. 1819-1822 [doi]
• Bacterial foraging oriented by particle swarm optimization strategy for PID tuningWael Mansour Korani. 1823-1826 [doi]
• Search for human competitive results in open ended automated synthesis of a primordial mechatronic systemSaheeb Ahmed Kayani. 1827-1830 [doi]
• Topology optimization of compliant mechanism using multi-objective particle swarm optimizationNikhil Padhye. 1831-1834 [doi]
• Interplanetary trajectory optimization with swing-bys using evolutionary multi-objective optimizationNikhil Padhye. 1835-1838 [doi]
• Agent Smith: a real-time game-playing agent for interactive dynamic gamesRyan K. Small. 1839-1842 [doi]
• A study for multi-objective fitness function for time series forecasting with intelligent techniquesAranildo Rodrigues Lima Junior. 1843-1846 [doi]
• Ultra high frequency financial dataMartin Victor Sewell, Wei Yan. 1847-1850 [doi]
• Technical market indicators optimization using evolutionary algorithmsPablo Fernández-Blanco, Diego J. Bodas-Sagi, Francisco J. Soltero, José Ignacio Hidalgo. 1851-1858 [doi]
• Non-linear factor model for asset selection using multi objective genetic programmingGhada Hassan. 1859-1862 [doi]
• ADANN: automatic design of artificial neural networksJuan Peralta, Germán Gutiérrez, Araceli Sanchís. 1863-1870 [doi]
• Design of stock trading system for historical market data using multiobjective particle swarm optimization of technical indicatorsAntonio C. Briza, Prospero C. Naval Jr.. 1871-1878 [doi]
• Applications of multi-objective evolutionary algorithms to air operations mission planningBrad Rosenberg, Marc Richards, John T. Langton, Sofya Tenenbaum, Daniel W. Stouch. 1879-1886 [doi]
• Evolving combat algorithms to control space ships in a 2D space simulation game with co-evolution using genetic programming and decision treesTiago Francisco, Gustavo Miguel Jorge dos Reis. 1887-1892 [doi]
• Evolving predator and prey behaviours with co-evolution using genetic programming and decision treesTiago Francisco, Gustavo Miguel Jorge dos Reis. 1893-1900 [doi]
• Evolving better satellite image compression and reconstruction transformsBrendan Babb, Frank Moore, Michael R. Peterson, Gary B. Lamont. 1901-1906 [doi]
• A differential evolution algorithm for optimizing signal compression and reconstruction transformsFrank W. Moore, Brendan J. Babb. 1907-1912 [doi]
• Emergent architecture in self organized swarm systems for military applicationsDustin J. Nowak, Gary B. Lamont, Gilbert L. Peterson. 1913-1920 [doi]
• Metaoptimization of the in-lining priority function for a compiler targeting a polymorphous computing architectureLaurence D. Merkle. 1921-1928 [doi]
• Automated network forensicsLaurence D. Merkle. 1929-1932 [doi]
• Comparing different modes of horizontal information transmission in stabilizing cooperation in different complex networksIvette C. Martínez, Klaus Jaffe. 1933-1938 [doi]
• Towards incremental social learning in optimization and multiagent systemsMarco Antonio Montes de Oca, Thomas Stützle. 1939-1944 [doi]
• Infection-based self-configuration in agent societiesNorman Salazar, Juan A. Rodríguez-Aguilar, Josep Lluís Arcos. 1945-1952 [doi]
• Exploring population geometry and multi-agent systems: a new approach to developing evolutionary techniquesCamelia Chira, Anca Gog, Dumitru Dumitrescu. 1953-1960 [doi]
• Autonomous agent behavior generation using multiobjective evolutionary optimizationDustin J. Nowak, Gary B. Lamont. 1961-1968 [doi]
• An agent-based collaborative evolutionary model for multimodal optimizationRodica Ioana Lung, Camelia Chira, Dumitru Dumitrescu. 1969-1976 [doi]
• On the effects of node duplication and connection-oriented constructivism in neural XCSFGerard David Howard, Larry Bull. 1977-1984 [doi]
• Recursive least squares and quadratic prediction in continuous multistep problemsDaniele Loiacono, Pier Luca Lanzi. 1985-1992 [doi]
• Supply chain management sales using XCSRMaria A. Franco, Ivette C. Martínez, Celso Gorrin. 1993-2000 [doi]
• Adapted Pittsburgh classifier system: building accurate strategies in non markovian environmentsGilles Énée, Mathias Peroumalnaïk. 2001-2008 [doi]
• Evolving prediction weights using evolution strategyTrung Hau Tran, Cédric Sanza, Yves Duthen. 2009-2016 [doi]
• A new approach for multi-label classification based on default hierarchies and organizational learningRosane M. M. Vallim, David E. Goldberg, Xavier Llorà, Thyago S. P. C. Duque, André C. P. L. F. Carvalho. 2017-2022 [doi]
• Towards increasing learning speed and robustness of XCSF: experimenting with larger offspring set sizesPatrick Stalph, Martin V. Butz. 2023-2030 [doi]
• First approach toward on-line evolution of association rules with learning classifier systemsAlbert Orriols-Puig, Jorge Casillas, Ester Bernadó-Mansilla. 2031-2038 [doi]
• Learning classifier systems for optimisation problems: a case study on fractal travelling salesman problemMaximiliano Tabacman, Natalio Krasnogor, Jaume Bacardit, Irene Loiseau. 2039-2046 [doi]
• Informative sampling for large unbalanced data setsZhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Josh Bongard. 2047-2054 [doi]
• Multiobjective optimization of a stent in a fluid-structure contextAdel Blouza, Laurent Dumas, Ibrahima M Baye. 2055-2060 [doi]
• Analysis of mammography reports using maximum variation samplingRobert M. Patton, Barbara Beckerman, Thomas E. Potok. 2061-2064 [doi]
• Interactive search of rules in medical data using multiobjective evolutionary algorithmsDaniela Zaharie, Diana Lungeanu, Flavia Zamfirache. 2065-2072 [doi]
• Towards an objective assessment of alzheimer s disease: the application of a novel evolutionary algorithm in the analysis of figure copying tasksAlex Hazell, Stephen L. Smith. 2073-2080 [doi]
• An information geometry perspective on estimation of distribution algorithms: boundary analysisLuigi Malagò, Matteo Matteucci, Bernardo Dal Seno. 2081-2088 [doi]
• A bivariate probabilistic model-building genetic algorithm for graph bipartitioningDirk Thierens. 2089-2092 [doi]
• Attack analysis & bio-inspired security framework for IPMultimedia subsystemAliya Awais, Muddassar Farooq, Muhammad Younus Javed. 2093-2098 [doi]
• Evolutionary facial feature selectionAaron K. Baughman. 2099-2104 [doi]
• A synergistic approach for evolutionary optimizationMaumita Bhattacharya. 2105-2110 [doi]
• Handling uncertainty with a real-coded EAMaumita Bhattacharya. 2111-2116 [doi]
• Reduced computation for evolutionary optimization in noisy environmentMaumita Bhattacharya. 2117-2122 [doi]
• Multi-objective memetic approach for flexible process sequencing problemsJian-Hong Chen, Jian-Hung Chen. 2123-2128 [doi]
• A comparison of multiobjective evolutionary algorithms with informed initialization and kuhn-munkres algorithm for the sailor assignment problemDipankar Dasgupta, German Hernandez, Deon Garrett, Pavan Kalyan Vejandla, Aishwarya Kaushal, Ramjee Yerneni, James Simien. 2129-2134 [doi]
• Incorporating model identifiability into equation discovery of ODE systemsDirk J. W. De Pauw, Bernard De Baets. 2135-2140 [doi]
• A fuzzy-genetic approach to network intrusion detectionTerrence P. Fries. 2141-2146 [doi]
• Towards memoryless model buildingDavid Iclanzan, Dumitru Dumitrescu. 2147-2152 [doi]
• Using feature-based fitness evaluation in symbolic regression with added noiseJanine H. Imada, Brian J. Ross. 2153-2158 [doi]
• Multi-task code reuse in genetic programmingWojciech Jaskowski, Krzysztof Krawiec, Bartosz Wieloch. 2159-2164 [doi]
• Bond-graphs + genetic programming: analysis of an automatically synthesized rotary mechanical systemSaheeb Ahmed Kayani, Muhammad Afzaal Malik. 2165-2168 [doi]
• Developing neural structure of two agents that play checkers using cartesian genetic programmingGul Muhammad Khan, Julian Francis Miller, David M. Halliday. 2169-2174 [doi]
• Potential fitness for genetic programmingKrzysztof Krawiec, PrzemysBaw Polewski. 2175-2180 [doi]
• Threshold selecting: best possible probability distribution for crossover selection in genetic algorithmsJörg Lässig, Karl Heinz Hoffmann, Mihaela Enachescu. 2181-2186 [doi]
• Self-managing agents for dynamic scheduling in manufacturingAna Madureira, Filipe Santos, Ivo Pereira. 2187-2192 [doi]
• Risk prediction and risk factors identification from imbalanced data with RPMBGA+Topon Kumar Paul, Ken Ueno, Koichiro Iwata, Toshio Hayashi, Nobuyoshi Honda. 2193-2198 [doi]
• Parameterizing pair approximations for takeover dynamicsJoshua L. Payne, Margaret J. Eppstein. 2199-2204 [doi]
• Evolutionary algorithm considering program size: efficient program evolution using grapeShinichi Shirakawa, Tomoharu Nagao. 2217-2222 [doi]
• A novel methodology for diversity preservation in evolutionary algorithmsGiovanni Squillero, Alberto Paolo Tonda. 2223-2226 [doi]
• Opportunistic evolution: efficient evolutionary computation on large-scale computational gridsKeith Sullivan, Sean Luke, Curt Larock, Sean Cier, Steven Armentrout. 2227-2232 [doi]
• Using quotient graphs to model neutrality in evolutionary searchDominic Wilson, Devinder Kaur. 2233-2238 [doi]
• Double-deck elevator system using genetic network programming with genetic operators based on pheromone informationLu Yu, Jin Zhou, Fengming Ye, Shingo Mabu, Kaoru Shimada, Kotaro Hirasawa, Sandor Markon. 2239-2244 [doi]
• Evolutionary computation: a unified approachKenneth De Jong. 2245-2258 [doi]
• Evolution strategies: basic introductionThomas Bäck. 2259-2276 [doi]
• Introduction to genetic algorithmsErik D. Goodman. 2277-2298 [doi]
• Introduction to genetic programming: tutorialJohn R. Koza. 2299-2338 [doi]
• Gecco 2008 grammatical evolution tutorialR. Muhammad Atif Azad, Conor Ryan. 2339-2366 [doi]
• Learning classifier systemsMartin V. Butz. 2367-2388 [doi]
• Probabilistic model-building genetic algorithmsMartin Pelikan. 2389-2416 [doi]
• Computational complexity and evolutionary computationThomas Jansen, Frank Neumann. 2417-2444 [doi]
• Constraint-handling techniques used with evolutionary algorithmsCarlos A. Coello Coello. 2445-2466 [doi]
• Evolutionary multiobjective optimizationEckart Zitzler, Kalyanmoy Deb. 2467-2486 [doi]
• Evolutionary practical optimizationKalyanmoy Deb. 2487-2516 [doi]
• Experimental research in evolutionary computationThomas Bartz-Beielstein, Mike Preuss. 2517-2534 [doi]
• Genetic algorithm theoryJonathan E. Rowe. 2535-2558 [doi]
• Genetic programming theoryRiccardo Poli. 2559-2588 [doi]
• No free lunchDarrell Whitley. 2589-2612 [doi]
• Representations for evolutionary algorithmsFranz Rothlauf. 2613-2638 [doi]
• An introduction to statistical analysis for evolutionary computationMark Wineberg, Steffen Christensen. 2639-2664 [doi]
• Ea-based test and verification of microprocessorsGiovanni Squillero. 2665-2688 [doi]
• An information perspective on evolutionary computationYossi Borenstein. 2689-2700 [doi]
• Cartesian genetic programmingJulian Francis Miller, Simon Harding. 2701-2726 [doi]
• Evolution strategies and related estimation of distribution algorithmsAnne Auger, Nikolaus Hansen. 2727-2740 [doi]
• Evolutionary computation & gamesMoshe Sipper. 2741-2776 [doi]
• Evolutionary design search, exploration and optimisationIan C. Parmee. 2777-2804 [doi]
• Evolutionary multiobjective combinatorial optimization (EMCO)Rajeev Kumar. 2805-2828 [doi]
• Evolving neural networksRisto Miikkulainen, Kenneth O. Stanley. 2829-2848 [doi]
• Generative and developmental systemsKenneth O. Stanley. 2849-2864 [doi]
• Quantum computingLee Spector. 2865-2894 [doi]
• Symbolic regressionMaarten Keijzer. 2895-2906 [doi]
• Theory of randomised search heuristics in combinatorial optimisation: an algorithmic point of viewCarsten Witt. 2907-2946 [doi]