Search Space Research Papers - Academia.edu (original) (raw)

In this paper, we address the problem of finding frequent itemsets in a database. Using the closed itemset lattice framework, we show that this problem can be reduced to the problem of finding frequent closed itemsets. Based on this... more

In this paper, we address the problem of finding frequent itemsets in a database. Using the closed itemset lattice framework, we show that this problem can be reduced to the problem of finding frequent closed itemsets. Based on this statement, we can construct efficient data mining algorithms by limiting the search space to the closed itemset lattice rather than the subset lattice. Moreover, we show that the set of all frequent closed itemsets suffices to determine a reduced set of association rules, thus addressing another important data mining problem: limiting the number of rules produced without information loss.We propose a new algorithm, called A-Close, using a closure mechanism to find frequent closed itemsets. We realized experiments to compare our approach to the commonly used frequent itemset search approach. Those experiments showed that our approach is very valuable for dense and/or correlated data that represent an important part of existing databases.

In this paper we describe EvoCK, a new approach to the application of genetic programming (GP) to planning. This approach starts with a traditional AI planner (Prodigy) and uses GP to acquire control rules to improve its efficiency. We... more

In this paper we describe EvoCK, a new approach to the application of genetic programming (GP) to planning. This approach starts with a traditional AI planner (Prodigy) and uses GP to acquire control rules to improve its efficiency. We also analyze two ways to introduce domain knowledge acquired by another method (Hamlet) into EvoCK: seeding the initial population and using a new operator (knowledge-based crossover). This operator combines genetic material from both an evolving population and a non-evolving population containing background knowledge. We tested these ideas in the blocksworld domain and obtained excellent results.

The covariancematrix adaptation evolution strategy (CMA-ES) is one of themost powerful evolutionary algorithms for real-valued single-objective optimization. In this paper, we develop a variant of the CMA-ES for multi-objective... more

The covariancematrix adaptation evolution strategy (CMA-ES) is one of themost powerful evolutionary algorithms for real-valued single-objective optimization. In this paper, we develop a variant of the CMA-ES for multi-objective optimization (MOO). We first introduce a single-objective, elitist CMA-ES using plus-selection and step size control based on a success rule. This algorithm is compared to the standard CMA-ES. The elitist CMA-ES turns out to be slightly faster on unimodal functions, but is more prone to getting stuck in sub-optimal local minima. In the new multi-objective CMAES (MO-CMA-ES) a population of individuals that adapt their search strategy as in the elitist CMA-ES is maintained. These are subject to multi-objective selection. The selection is based on non-dominated sorting using either the crowding-distance or the contributing hypervolume as second sorting criterion. Both the elitist single-objective CMA-ES and the MO-CMA-ES inherit important invariance properties, ...

Interest in multimodal optimization function is expanding rapidly since real-world optimization problems often require the location of multiple optima in the search space. In this context, fitness sharing has been used widely to maintain... more

Interest in multimodal optimization function is expanding rapidly since real-world optimization problems often require the location of multiple optima in the search space. In this context, fitness sharing has been used widely to maintain population diversity and permit the investigation of manly peaks in the feasible domain. This paper reviews various strategies of sharing and proposes new recombination schemes to improve its efficiency. Some empirical results are presented for high and a limited number of fitness function evaluations. Finally, the study compares the sharing method with other niching techniques

A classical problem of imaging—the matting problem—is sepa-ration of a non-rectangular foreground image from a (usually) rectangular background image—for example, in a film frame, extraction of an actor from a background scene to allow... more

A classical problem of imaging—the matting problem—is sepa-ration of a non-rectangular foreground image from a (usually) rectangular background image—for example, in a film frame, extraction of an actor from a background scene to allow substitu-tion of a different background. Of ...

Abstract-A new optimization method has been proposed by Kennedy et ul. in [7, 81, called Parti-cle Swarm Optimization (PSO). This approach com-bines social psychology principles and evolution-ary computation. It has been applied... more

Abstract-A new optimization method has been proposed by Kennedy et ul. in [7, 81, called Parti-cle Swarm Optimization (PSO). This approach com-bines social psychology principles and evolution-ary computation. It has been applied success-fully to nonlinear function ...

Recently several researchers have investi- gated techniques for using data to learn Bayesian networks containing compact rep- resentations for the conditional probability distributions (CPDs) stored at each node. The majority of this work... more

Recently several researchers have investi- gated techniques for using data to learn Bayesian networks containing compact rep- resentations for the conditional probability distributions (CPDs) stored at each node. The majority of this work has concentrated on using decision-tree representations for the CPDs. In addition, researchers typi- cally apply non-Bayesian (or asymptotically Bayesian) scoring functions such as MDL to evaluate the

Autonomous unmanned air vehicle flight con-trol systems require robust path generation to ac-count for terrain obstructions, weather, and moving threats such as radar, jammers, and unfriendly air-craft. In this paper, we outline a... more

Autonomous unmanned air vehicle flight con-trol systems require robust path generation to ac-count for terrain obstructions, weather, and moving threats such as radar, jammers, and unfriendly air-craft. In this paper, we outline a feasible, hierarchal approach for real-time motion ...