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» Representation and structural biases in CGP
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CEC
2009
IEEE
13 years 11 months ago
Representation and structural biases in CGP
— An evolutionary algorithm automatically discovers suitable solutions to a problem, which may lie anywhere in a large search space of candidate solutions. In the case of Genetic...
Andrew J. Payne, Susan Stepney
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
13 years 10 months ago
Finding needles in haystacks is harder with neutrality
This research presents an analysis of the reported successes of the Cartesian Genetic Programming method on a simplified form of the Boolean parity problem. We show the method of...
M. Collins
CORR
2010
Springer
124views Education» more  CORR 2010»
13 years 1 months ago
Lattice model refinement of protein structures
To find the best lattice model representation of a given full atom protein structure is a hard computational problem. Several greedy methods have been suggested where results are ...
Martin Mann, Alessandro Dal Palù
IEAAIE
2005
Springer
13 years 10 months ago
Structural Advantages for Ant Colony Optimisation Inherent in Permutation Scheduling Problems
When using a constructive search algorithm, solutions to scheduling problems such as the job shop and open shop scheduling problems are typically represented as permutations of the...
James Montgomery, Marcus Randall, Tim Hendtlass
ML
1998
ACM
131views Machine Learning» more  ML 1998»
13 years 4 months ago
Learning from Examples and Membership Queries with Structured Determinations
It is well known that prior knowledge or bias can speed up learning, at least in theory. It has proved di cult to make constructive use of prior knowledge, so that approximately c...
Prasad Tadepalli, Stuart J. Russell