105 citations · 399 across the 23 of their papers we have counts for
24 papers
Liquid State Genetic Programming
Mihai Oltean
A new Genetic Programming variant called Liquid State Genetic Programming (LSGP) is proposed in this paper. LSGP is a hybrid method combining a dynamic memory for storing the input…
A comparison of several AI techniques for authorship attribution on Romanian texts
Sanda Maria Avram, Mihai Oltean
Determining the author of a text is a difficult task. Here we compare multiple AI techniques for classifying literary texts written by multiple authors by taking into account a lim…
Multi Expression Programming for solving classification problems
Mihai Oltean
Multi Expression Programming (MEP) is a Genetic Programming variant which encodes multiple solutions in a single chromosome. This paper introduces and deeply describes several stra…
Improving the Search by Encoding Multiple Solutions in a Chromosome
Mihai Oltean
We investigate the possibility of encoding multiple solutions of a problem in a single chromosome. The best solution encoded in an individual will represent (will provide the fitne…
Evolving Evolutionary Algorithms with Patterns
Mihai Oltean
A new model for evolving Evolutionary Algorithms (EAs) is proposed in this paper. The model is based on the Multi Expression Programming (MEP) technique. Each MEP chromosome encode…
Solving classification problems using Traceless Genetic Programming
Mihai Oltean
Traceless Genetic Programming (TGP) is a new Genetic Programming (GP) that may be used for solving difficult real-world problems. The main difference between TGP and other GP techn…