Inductive Logic Programming (ILP) integrates the techniques from traditional machine learning and logic programming to construct logic programs from training examples. Most existing systems employâ€¦ (More)

The knowledge acquisition bottleneck greatly obstructs the development of knowledge-based systems. One popular approach to knowledge acquisition uses inductive concept learning to derive knowledgeâ€¦ (More)

As a typical combinatorial optimization problem, the traveling salesman problem (TSP) has attracted extensive research interest. In this paper, we develop a self-organizing map (SOM) with a novelâ€¦ (More)

Evolutionary algorithms (EAs) are effective and robust methods for solving many practical problems such as feature selection, electrical circuit synthesis, and data mining. However, they may executeâ€¦ (More)

Program induction generates a computer program that can produce the desired behavior for a given set of situations. Two of the approaches in program induction are inductive logic programming (ILP)â€¦ (More)

We have developed a new approach (MDLEP) to learning Bayesian network structures based on the Minimum Description Length (MDL) principle and Evolutionary Programming (EP). It employs a MDL metric,â€¦ (More)

Genetic Programming (GP) is a method of automatically inducing S-expression in LISP to perform specified tasks. The problem of inducing programs can be reformulated as a search for a highly fitâ€¦ (More)

In this paper, we report a parallel hybrid genetic algorithm (HGA) on consumer-level graphics cards. HGA extends the classical genetic algorithm by incorporating the Cauchy mutation operator fromâ€¦ (More)