Abstract New algorithms are constantly developed in search of better or faster results. Many variants of code are often tried while searching for the best solution. When the number...
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
This paper presents a predictable and grouped genetic algorithm (PGGA) for job scheduling. The novelty of the PGGA is twofold: (1) a job workload estimati...
This paper introduces a novel genetic algorithm strategy based on the reuse of chromosomes from previous generations in the creation of offspring individuals. A number of chromoso...