In　the　Argumentation-based　negotiation　of　agent,　it　is　important　to　enhance　the　agent＇s　ability　according　to　the　environment,　which　would　improve　the　argumentation　efficiency　significantly.　Introducing　Bayesian　learning　model　to　select　arguments　in　Argumentation-based　negotiation,　the　agent　is　able　to　learn　and　adjust　itself　according　to　a　dynamic　environment.　This　helps　in　making　more　rational　and　scientific　choice　for　advancing　efficiency　of　argumentation,　when　it　is　facing　a　variety　of　options　for　sending　arguments.　Finally,　an　example　was　presented　for　showing　the　rationality　and　validity　of　the　model.