Aiming　at　the　problem　about　the　movement　balance　control　of　two-wheeled　self-balancing　mobile　robot,　a　learning　algorithm　that　it　is　made　up　of　BP　neural　network　and　eligibility　traces　based　on　the　operant　conditioning　theory　is　put　forward　as　a　learning　mechanism　of　the　two-wheeled　robot.　The　algorithm　utilizes　the　characters　of　eligibility　traces　about　quicker　learning　speed,　higher　reliability　and　ability　in　resolving　effect　about　delay,　so　that　the　two-wheeled　robot　can　obtain　the　movement　balance　skills　of　controlling　like　a　human　or　animal　by　interacting,　studying　and　training　with　unknown　environmental,　and　realize　the　movement　balance　control　of　the　two-wheeled　robot　by　using　the　complex　learning　algorithm.　Finally,　a　simulation　experiment　is　done　and　the　simulation　results　show　that　a　learning　mechanism　of　the　complex　learning　algorithm　can　embodies　the　stronger　skills　of　self-learning　and　abilities　of　balance　control　of　the　robot,　and　it　also　has　the　higher　research　significance　in　theory　and　the　application　value　in　project.