— The application of on-line learning techniques to modern computer games is a promising research direction. In fact, they can be used to improve the game experience and to achie...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
— In this paper, we propose a new algorithm, named JACC-G, for large scale optimization problems. The motivation is to improve our previous work on grouping and adaptive weightin...
Zhenyu Yang, Jingqiao Zhang, Ke Tang, Xin Yao, Art...
—Developing systems that support people in everyday life in a discrete and effective way is an ultimate goal of a new generation of technical systems. Physiological computing rep...
— Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of a simplified form of traditional particle swarm optimization (PSO) without the i...
In this Chapter we present the modification of a Differential Evolution algorithm to solve constrained optimization problems. The changes include a deterministic and a self-adapti...
— Regulatory networks are complex networks. This paper addresses the challenge of modelling these networks. The Boolean representation is chosen and supported as a representation...
Cristina Costa Santini, Gunnar Tufte, Pauline C. H...
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
— We extend the Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) by collaborative concepts from Particle Swarm Optimization (PSO). The proposed Particle Swarm CMA-ES...
— By dividing the multiobjective optimization of the decision space into several small regions, this paper proposes multi-objective optimization algorithm based on sub-regional s...