Abstract. This work merges ideas from two very different areas: Particle Swarm Optimisation and Evolutionary Game Theory. In particular, we are looking to integrate strategies from...
Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continu...
Niching techniques play an important role in evolutionary algorithms. Existing niching methods often require userspecified parameters, limiting their usefulness. This paper propos...
Cancer chemotherapy is a complex treatment mode that requires balancing the benefits of treating tumours using anti-cancer drugs with the adverse toxic side-effects caused by these...
Andrei Petrovski, Bhavani Sudha, John A. W. McCall
Particle Swarm Optimisation (PSO) uses a population of particles that fly over the fitness landscape in search of an optimal solution. The particles are controlled by forces tha...
Riccardo Poli, Cecilia Di Chio, William B. Langdon
Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continu...
A method is presented that allows one to exactly determine all the characteristics of a PSO’s sampling distribution and explain how it changes over time, in the presence stochas...
—This paper describes a distributed particle swarm optimisation algorithm (PSO) based on peer-to-peer computer networks. A number of modifications are made to the more tradition...
Ian Scriven, Andrew Lewis, David Ireland, Junwei L...
Abstract. This paper presents and discusses the results of the latest developments of the MapPSO system, which is an ontology alignment approach that is based on discrete particle ...
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...