This paper presents a methodology to design optimized electronic systems from high abstraction level descriptions. The methodology uses Genetic Programming in addition to high-leve...
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...
Abstract— We present a grammar-based genetic programming framework for the solving the timetabling problem via the evolution of constructive heuristics. The grammar used for prod...
Abstract. Nested data-parallel programs often have large memory requirements due to their high degree of parallelism. Piecewise execution is an implementation technique used to min...
Abstract. The mutation distribution of evolutionary algorithms usually is oriented at the type of the search space. Typical examples are binomial distributions for binary strings i...