In　argumentation-based　negotiation　based　on　multi-agent,　if　a　negotiator　agent　is　endowed　with　ability　of　self-learning,　then　it　can　acquire　much　more　information　about　opponent＇s　costs　and　benefits　to　achieve　the　purpose　of　improving　negotiated　efficiency.　This　paper　discusses　the　problem　of　adaptive　strategy　in　intelligent　argumentation-based　negotiation,　presents　a　generating　process　of　adaptive　strategy,　optimizes　and　improves　the　process　by　using　a　method　of　machine　learning　to　help　negotiator　to　determine　valid　candidate　concessional　attributes　and　concessional　values.　Finally,　this　paper　also　describes　an　implementing　process　of　the　strategy　model　and　explains　it　in　details.　The　research　results　of　this　paper　provide　new　ideas　and　measures　for　solving　the　problem　that　how　to　generate　reasonable　adaptive　strategies　in　argumentation-based　negotiation.　©　2012　IEEE.