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GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
14 years 1 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
IPL
2007
78views more  IPL 2007»
13 years 7 months ago
Ensuring the quasi-termination of needed narrowing computations
We present a characterization of first-order functional programs which are quasiterminating w.r.t. the symbolic execution mechanism of needed narrowing, i.e., computations in the...
J. Guadalupe Ramos, Josep Silva, Germán Vid...
ICAI
2007
13 years 9 months ago
Dynamic Programming Algorithm for Training Functional Networks
Abstract— The paper proposes a dynamic programming algorithm for training of functional networks. The algorithm considers each node as a state. The problem is formulated as find...
Emad A. El-Sebakhy, Salahadin Mohammed, Moustafa E...
WCE
2007
13 years 9 months ago
Game Theory Using Genetic Algorithms
—In this paper we used genetic algorithms to1 find the solution of game theory. We proposed new method foe solving game theory and find the optimal strategy for player A or playe...
Ismail A. Ismail, Nabawia A. El Ramly, M. M. El Ka...
ENGL
2007
191views more  ENGL 2007»
13 years 7 months ago
Application of Genetic Algorithm to the Optimization of Gain of Magnetized Ferrite Microstrip Antenna
The application of Genetic Algorithm (GA) to the optimization of gain of microstrip antenna, fabricated on ferrite substrate, biased externally by a steady magnetic field, is repor...
Neela Chattoraj, Jibendu Sekhar Roy