Titlebook: Genetic and Evolutionary Computation — GECCO 2004; Genetic and Evolutio Kalyanmoy Deb Conference proceedings 2004 Springer-Verlag Berlin He

圣歌

A Hybrid Ant Colony Optimisation Technique for Dynamic Vehicle Routings uncertain. The problem is expressed as a bi-criterion optimisation with the mutually exclusive aims of minimising both the total mean transit time and the total variance in transit time. In this paper we introduce a hybrid dynamic programming – ant colony optimisation technique to solve this probl

oblique

Cooperative Problem Solving Using an Agent-Based Market we investigate the efficacy of a novel market-based aggregation technique in addressing this problem. An incremental transaction-based protocol is introduced where agents establish links by buying and selling from each other. Market transactions equate to agents coordinating their plans and sharing

地牢

Cultural Evolution for Sequential Decision Tasks: Evolving Tic–Tac–Toe Players in Multi–agent System of experiments involving populations of agents that evolve to play games of tic–tac–toe. The focus of the paper is to propose that cultural learning, i.e. the passing of information from one generation to the next by non–genetic means, is a better approach than population learning alone, i.e. the p

燈絲

Artificial Life and Natural Intelligenced to motivate a journey down the .. First, the origins of brain structures and dynamics exhibit considerable emergence at phylogenic, epigenetic, and ontogenetic levels. Second, ALife complexity measures have interesting parallels in theoretical neuroscience. Finally, the cerebral internalization of

狗舍

Bluenome: A Novel Developmental Model of Artificial Morphogenesisopment, instantiating a subset of two-dimensional Cellular Automata. The Bluenome model is cast as a general model, one which generates organizational topologies for finite sets of component types, assuming only local interactions between components. Its key feature is that there exists no relation

Pcos971

Adaptively Choosing Neighbourhood Bests Using Species in a Particle Swarm Optimizer for Multimodal Fl optimization problems. In the proposed species-based PSO (SPSO), the swarm population is divided into species subpopulations based on their similarity. Each species is grouped around a dominating particle called the species seed. At each iteration step, species seeds are identified from the entire

concentrate

BIAS

不成比例

gerrymander