For　the　problems　related　to　market　equilibrium　in　complex　market　environments,　analyses　are　conducted　in　the　past,　using　some　mathematical　models　and　the　game　theory.　These　methods　are　based　on　the　economic　structural　equations　themselves,　ignoring　the　interactions　between　economic　subjects,　and　the　hypothesis　of　subject　homogeneity　has　no　reference　in　the　real　world.　On　contrast,　this　paper　proposes　a　multi-agent　simulation　model,　from　the　microscopic　point　of　view.　In　such　simulation,　agents　interact　with　each　other,　and　the　decisions　are　made　by　agent-embedded　AI　systems,　the　Q-network.　Therefore,　there　is　no　need　to　elaborate　the　behavioral　rule　for　each　agent,　or　manually　set　up　too　many　assumptions.　This　paper　assumes　that　the　simulated　market　operates　in　a　hypothetical　way,　in　which　there　are　two　types　of　economic　entities,　namely,　banks　and　enterprises.　Banks　and　enterprises　lending　behaviors　lead　to　a　symbiotic　relationship　between　the　banks　and　the　enterprises,　while　business-to-business　transactions　make　the　enterprises　symbiotically　compete　with　each　other.　In　the　experiment,　the　observed　behavior　of　each　agent　can　be　reasonably　explained.　Agents　endogenously　generate　intelligent　behavioral　patterns　compatible　with　the　environment.　Therefore,　this　AI-based　method　can　replace　the　artificially　designated　decision-making　strategy　in　simulations　of　market,　thus　facilitating　related　economic　researches.　©　2019　IEEE.