In　this　paper,　we　introduce　the　swarm　intelligence　methods　into　the　evolutionary　dynamics,　and　have　studied　the　impact　of　swarm　intelligent　algorithm　on　the　evolution　of　cooperation　among　selfish　individuals　in　the　continuous　version　of　spatial　public　goods　games　(PGG).　We　update　an　individual＇s　strategy　according　to　the　memory　which　records　the　most　successful　individual　strategy　in　the　past　(referred　to　as　its　personal　best　strategy)　as　well　as　the　knowledge　of　the　best　current　strategy　found　by　its　nearest　neighbors　(referred　to　as　the　neighborhood　best　strategy).　Through　extensive　simulations,　we　find　that　the　introduction　of　swarm　intelligence　into　PGG　can　promote　cooperation　strongly.　Other　pertinent　quantities　such　as　the　time　evolution　of　cooperator　density,　the　spatial　distribution　of　strategies　and　the　updated　velocities　are　also　investigated.　©　2017　Elsevier　Inc.