RT Conference Proceedings
T1 Coevolutive adaptation of fitness landscape for solving the testing problem
A1 Berlanga de Jesús, Antonio
A1 Isasi, Pedro
A1 Sanchis de Miguel, María Araceli
A1 Molina López, José Manuel
AB A general framework, called Uniform Coevolution, is introduced to overcome the testing problem in evolutionary computation methods. This framework is based on competitive evolution ideas where the solution and example sets are evolving by means of a competition to generate difficult test beds for the solutions in a gradual way. The method has been tested with two different problems: the robot navigation problem and the density parity problem in cellular automata. In both test cases using evolutive methods, the examples used in the learning process biased the solutions found. The main characteristics of the Uniform Coevolution method are that it smoothes the fitness landscape and, that it obtains “ideal learner examples”. Results using uniform coevolution show a high value of generality, compared with non co-evolutive approaches.
PB IEEE
SN 0-7803-6583-6
SN 1062-922X
YR 2000
FD 2000-10
LK http://hdl.handle.net/10016/4056
UL http://hdl.handle.net/10016/4056
LA eng
NO IEEE International Conference on Systems, Man, and Cybernetics. Nashville, TN, 8-11 October 2000
DS e-Archivo
RD 30 abr. 2024