Complex　economic　system　theory　studies　the　socio-economic　system　in　a　dynamic,　complex　ideas.　It　is　a　more　comprehensive　economic　theory　established　in　non-equilibrium　basis.　At　present,　under　the　guidance　of　complex　economic　system　theory,　multi-agent　based　modeling　and　simulation　is　a　universal　research　method　to　study　economic　system.　However,　the　agent＇s　behavior　usually　is　fixed　according　to　the　simulation　software＇s　setting,　which　is　difficult　to　explain　the　phenomena　of　feedback　and　emergence　in　the　economic　system.　To　address　this　problem,　we　first　design　a　simulation　economic　system.　In　the　system,　there　are　two　types　of　abstract　micro　economic　agents,　bank　and　enterprise.　An　improved　version　of　Deep　Q-Network　(DQN),　Deep　Recurrent　Q-Network　(DRQN)　was　introduced　to　handle　the　decision-making　of　micro　economic　agents.　Finally,　we　studied　the　observed　behavior　of　agents　in　the　experiment.　The　experimental　results　show　that　the　behavior　of　economic　agents　can　actively　adapt　to　changes　in　the　system　environment　and　continue　to　be　optimized　with　the　accumulation　of　experience.　Because　of　taking　non-fixed　decision-making　strategies,　this　method　can　reflect　the　phenomena　of　internal　feedback　and　emergence　in　economic　system.　Therefore,　simulation　based　on　DRQN　is　a　simulation　method　that　can　better　reflect　agent　decision-making　in　real　economic　system　and　it　can　play　an　important　role　in　the　study　of　complex　economic　system.　©　2020　IEEE.