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EMO
2005
Springer
126views Optimization» more  EMO 2005»
16 years 5 days ago
The Evolution of Optimality: De Novo Programming
Abstract. Evolutionary algorithms have been quite effective in dealing with single-objective “optimization” while the area of Evolutionary Multiobjective Optimization (EMOO) h...
Milan Zeleny
GECCO
2009
Springer
110views Optimization» more  GECCO 2009»
15 years 11 months ago
EMO shines a light on the holes of complexity space
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
Núria Macià, Albert Orriols-Puig, Es...
EMO
2009
Springer
143views Optimization» more  EMO 2009»
15 years 4 months ago
Adapting to the Habitat: On the Integration of Local Search into the Predator-Prey Model
Traditionally, Predator-Prey Models--although providing a more nature-oriented approach to multi-objective optimization than many other standard Evolutionary Multi-Objective Algori...
Christian Grimme, Joachim Lepping, Alexander Papas...
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 10 months ago
Evolving distributed agents for managing air traffic
Air traffic management offers an intriguing real world challenge to designing large scale distributed systems using evolutionary computation. The ability to evolve effective air t...
Adrian K. Agogino, Kagan Tumer
FOGA
1990
15 years 7 months ago
A Hierarchical Approach to Learning the Boolean Multiplexer Function
This paper describes the recently developed genetic programming paradigm which genetically breeds populations of computer programs to solve problems. In genetic programming, the i...
John R. Koza