In　this　paper,　the　intelligent　and　online　value　iteration　(VI)　algorithms　are　developed　to　solve　the　optimal　control　problem　for　nonlinear　discrete-time　systems.　First,　the　intelligent　VI　algorithm　combines　the　advantages　of　traditional　VI　initialized　by　the　zero　cost　function　and　stabilizing　VI　initialized　by　the　admissible　control　policy.　The　traditional　VI　is　easy　to　implement　and　can　provide　the　initial　admissible　control　policy　for　the　stabilizing　VI.　Meanwhile,　stabilizing　VI　can　guarantee　all　control　policies　are　admissible.　Second,　based　on　the　concept　of　the　attraction　domain,　an　online　value　iteration　algorithm　is　proposed　to　regulate　the　closed-loop　system　by　using　immature　control　policies　rather　than　the　fixed　optimal　control　policy.　It　ensures　that　the　state　trajectory　converges　to　the　origin　of　the　attraction　domain.　Finally,　simulations　are　carried　out　and　the　results　show　the　effectiveness　of　the　two　new　VI　algorithms.