Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
A compiling genetic programming system that directly manipulates the machine code
Advances in genetic programming
Bayesian learning of probabilistic language models
Bayesian learning of probabilistic language models
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
A Representation Scheme To Perform Program Induction in a Canonical Genetic Algorithm
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming
Selected Papers from the 5th European Conference on Artificial Evolution
Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
Probabilistic distribution models for EDA-based GP
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Probabilistic CFG with latent annotations
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
AntTAG: a new method to compose computer programs using colonies of ants
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Scalable estimation-of-distribution program evolution
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Probabilistic incremental program evolution
Evolutionary Computation
An adverse interaction between crossover and restricted tree depth in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
A linear estimation-of-distribution GP system
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Inferring parameters and structure of latent variable models by variational bayes
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Bayesian automatic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
A Bayesian Network Approach to Program Generation
IEEE Transactions on Evolutionary Computation
Structural difficulty in estimation of distribution genetic programming
Proceedings of the 13th annual conference on Genetic and evolutionary computation
GPDL: a framework-independent problem definition language for grammar-guided genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Estimation of distribution algorithms are evolutionary algorithms using probabilistic techniques instead of traditional genetic operators. Recently, the application of probabilistic techniques to program and function evolution has received increasing attention, and this approach promises to provide a strong alternative to the traditional genetic programming techniques. Although a probabilistic context-free grammar (PCFG) is a widely used model for probabilistic program evolution, a conventional PCFG is not suitable for estimating interactions among nodes because of the context freedom assumption. In this paper, we have proposed a new evolutionary algorithm named programming with annotated grammar estimation based on a PCFG with latent annotations, which allows this context freedom assumption to be weakened. By applying the proposed algorithm to several computational problems, it is demonstrated that our approach is markedly more effective at estimating building blocks than prior approaches.