Peer-to-peer　energy　trading　among　microgrids　has　many　advantages,　e.g.,　increasing　the　utilization　of　renewable　energies,　reducing　the　dependence　on　the　main　grid　and　reducing　energy　cost.　In　this　paper,　we　investigate　a　peer-to-peer　energy　trading　problem　among　microgrids　under　uncertainties.　To　be　specific,　each　microgrid　intends　to　maximize　its　own　utility　in　a　local　peer-to-peer　energy　market.　Due　to　the　existence　of　uncertainties　in　renewable　energy　output　and　power　demand　of　all　microgrids,　and　temporally-coupled　constraints　related　to　energy　storage　devices,　it　is　very　challenging　to　develop　an　optimal　energy　trading　policy　for　each　microgrid.　To　achieve　the　above　aim,　we　propose　a　multiagent　deep　deterministic　policy　gradient　(MADDPG)-based　energy　trading　algorithm,　which　can　help　to　find　the　optimal　policy　for　each　microgrid　without　requiring　the　generation　and　load　information　of　other　microgrids.　Moreover,　blockchain　is　adopted　to　guarantee　the　integrity　of　energy　transaction　data.　Simulation　results　show　the　effectiveness　of　the　proposed　algorithm　in　the　aspect　of　reducing　energy　cost　and　ensuring　the　security　of　transaction　data.　©　2020　IEEE.