This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
In this paper, we utilize a predator-prey model in order to identify characteristics of single-objective variation operators in the multi-objective problem domain. In detail, we a...
Christian Grimme, Joachim Lepping, Alexander Papas...
Particle Swarm Optimization (PSO) technique proved its ability to deal with very complicated optimization and search problems. This paper proposes a new particle swarm variant whi...
Motivation Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines a...
Recent algorithmic advances in Boolean satisfiability (SAT), along with highly efficient solver implementations, have enabled the successful deployment of SAT technology in a wi...