Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Learning Bayesian networks with local structure
Learning in graphical models
Morphing: combining structure and randomness
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
Evolutionary algorithms for the satisfiability problem
Evolutionary Computation
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
Genetic Algorithm Behavior in the MAXSAT Domain
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications (Studies in Computational Intelligence)
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Analyzing probabilistic models in hierarchical BOA on traps and spin glasses
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Hierarchical BOA solves ising spin glasses and MAXSAT
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Intelligent bias of network structures in the hierarchical BOA
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Correlation guided model building
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Engineering Applications of Artificial Intelligence
Network crossover performance on NK landscapes and deceptive problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
A priori knowledge integration in evolutionary optimization
EA'09 Proceedings of the 9th international conference on Artificial evolution
Performance of network crossover on NK landscapes and spin glasses
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Sensibility of linkage information and effectiveness of estimated distributions
Evolutionary Computation
Estimation of distribution algorithms: from available implementations to potential developments
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Hybrid Estimation of Distribution Algorithm for the Quay Crane Scheduling Problem
Applied Soft Computing
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Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling probabilistic models of promising candidate solutions. While the primary goal of applying EDAs is to discover the global optimum (or an accurate approximation), any EDA also provides us with a sequence of probabilistic models, which hold a great deal of information about the problem. Although using problem-specific knowledge has been shown to significantly improve performance of EDAs and other evolutionary algorithms, this readily available source of information has been largely ignored by the EDA community. This paper takes the first step towards the use of probabilistic models obtained by EDAs to speed up the solution of similar problems in the future. More specifically, we propose two approaches to biasing model building in the hierarchical Bayesian optimization algorithm (hBOA) based on knowledge automatically learned from previous runs on similar problems. We show that the methods lead to substantial speedups and argue that they should work well in other applications that require solving a large number of problems with similar structure.