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» Adapting binary fitness functions in Genetic Algorithms
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AEI
1999
134views more  AEI 1999»
13 years 10 months ago
Automatic design synthesis with artificial intelligence techniques
Design synthesis represents a highly complex task in the field of industrial design. The main difficulty in automating it is the definition of the design and performance spaces, i...
Francisco J. Vico, Francisco J. Veredas, Jos&eacut...
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
14 years 2 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson
TEC
2002
101views more  TEC 2002»
13 years 10 months ago
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
This paper proposes a novel evolutionary algorithm inspired by quantum computing, called a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and principl...
Kuk-Hyun Han, Jong-Hwan Kim
GECCO
2004
Springer
118views Optimization» more  GECCO 2004»
14 years 4 months ago
Adaptive Sampling for Noisy Problems
Abstract. The usual approach to deal with noise present in many realworld optimization problems is to take an arbitrary number of samples of the objective function and use the samp...
Erick Cantú-Paz
ICCS
2007
Springer
14 years 2 months ago
Adaptive Sparse Grid Classification Using Grid Environments
Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the fe...
Dirk Pflüger, Ioan Lucian Muntean, Hans-Joach...