In　this　paper,　we　propose　a　cooperative　learning　algorithm　for　Multi-category　classification　which　is　decomposed　into　two　sub-optimization　problems　by　using　the　support　vector　machine　technique.　The　proposed　cooperative　learning　algorithm　consists　of　two　single　learning　algorithms　and　each　sub-optimization　problem　is　solved　by　one　of　them.　Unlike　the　cooperative　neural　network,　the　proposed　cooperative　learning　algorithm　is　discrete　time,　instead　of　continuous　time.　Therefore,　the　proposed　cooperative　learning　algorithm　has　a　faster　convergence　speed　than　the　cooperative　neural　network　for　Multi-category　classification　learning.　Simulation　results　show　the　computational　performance　of　the　proposed　cooperative　learning　algorithm　for　multiclass　classification　learning.　©　2010　IEEE.