We dene ve cooperation mechanisms in Particle Swarm Optimisation,

loosely inspired by some models occurring in nature, and based on two quan-

tities: a help matrix, and a reputation vector. We call these ve mechanisms,

respectively, Reciprocity, Vicinity, Kin, Reputation, and Anybody. It ap-

pears that Kin is better than the rest by a slight margin, but needs more

parameters that have to be tuned (mutation and selection). However, Reci-

procity, with less parameters, shows almost equivalent performance. The

appendix gives some details about fair comparison of success rates, and the

concepts of valued topology and chains of information, which may be worth

further investigation.