This　paper　constructs　a　learning　probabilistic　automata　(PA)　model　with　response　of　operant　conditioning　(OC)　behavior,　which　used　for　simulating　skinner-pigeon　experiment.　The　PA　model　with　OC　is　a　form　of　animal　learning　in　that　it　allows　an　agent　to　adapt　its　actions　to　gain　maximally　from　the　environment　while　only　being　rewarded　for　correct　performance.　The　learning　mechanism　achieved　by　design　probability　of　action　selection,　which　is　updated　by　the　information　of　reward　and　punishment　form　the　environment,　and　then　the　agent　select　an　action　random　according　to　the　probability　of　action　selection.　We　apply　our　model　to　skinner-pigeon　experiment,　the　peck　button　task.　The　pigeon　learn　this　task　in　stages.　In　simulation,　our　model　also　acquires　the　task　in　a　similar　manner.