An　intelligent　home　energy　management　system　was　proposed.　Reinforcement　learning　and　a　markov　prediction　model　were　used　to　help　the　system　make　decisions.　The　Markov　model　predicted　the　future　state　of　users　or　the　weather,　and　the　intelligent　decisionmaking　support　system　sent　signals　to　local　controllers　to　control　furniture.　This　work　benefits　energy　management　because　if　the　system　knows　the　user＇s　next　state,　it　can　control　a　specific　appliance　to　save　energy.　Meanwhile,　if　the　system　can　predict　the　weather,　the　house　can　use　green　energy　rationally.　The　proposed　energy　management　system　could　be　applied　in　an　intelligent　house,　city　energy　management　systems,　and　building　energy　management.　The　state　prediction　helped　the　decision-making　system　make　accurate　and　rational　decisions.　©　Published　under　licence　by　IOP　Publishing　Ltd.