311 search results - page 3 / 63 » Improving the performance of evolutionary algorithms for dec... |
NABIC
2010
13 years 2 months ago
2010
A new design method for Cellular automata (CA) rules are described. We have already proposed a method for designing the transition rules of two-dimensional 256-state CA for graysca...
EVOW
2000
Springer
13 years 11 months ago
2000
Springer
Ant Colony Optimization is an evolutionary method that has recently been applied to scheduling problems. We propose an ACO algorithm for the Single Machine Total Weighted Tardiness...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
PKDD
2004
Springer
14 years 24 days ago
2004
Springer
Ideally, a multi-strategy learning algorithm performs better than its component approaches. RISE is a multi-strategy algorithm that combines rule induction and instance-based learn...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
Trading rules are widely used by practitioners as an effective means to mechanize aspects of their reasoning about stock price trends. However, due to the simplicity of these rule...