— Self Modifying CGP (SMCGP) is a developmental form of Cartesian Genetic Programming(CGP). It differs from CGP by including primitive functions which modify the program. Beginni...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
— In a real-world, labor market consist of employer and employee, and these individuals form relationship through mutual interactions. This paper mainly focuses on development of...
—We conduct an evolutionary simulation to explore the coevolution of language and a language-related ability, intentionality sharing. Our simulation shows that during the evoluti...
— We propose a robot path planning method based on particle swarm optimization in an uncertain environment. We consider the case that a robot’s cognition to its environment is ...
Abstract— A combination of backpropagation and neuroevolution is used to train a neural network visual controller for agents in the Quake II environment. The agents must learn to...
Abstract— Tuning the parameters of an evolutionary algorithm (EA) to a given problem at hand is essential for good algorithm performance. Optimizing parameter values is, however,...
- Very recently bacterial foraging has emerged as a powerful technique for solving optimization problems. In this paper, we introduce a micro-bacterial foraging optimization algori...
— Hyper-heuristics or “heuristics to chose heuristics” are an emergent search methodology that seeks to automate the process of selecting or combining simpler heuristics in o...
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...
Alexander E. I. Brownlee, John A. W. McCall, Siddh...
Abstract— Peer-to-peer based distributed computing environments can be expected to be dynamic to greater of lesser degree. While node losses will not usually lead to catastrophic...