In　this　paper,　we　develop　an　event-Triggered　optimal　learning　algorithm　based　on　the　dual　heuristic　dynamic　programming　(DHP)　framework　to　solve　a　constrained　nonzero-sum　game　problem　with　discrete-Time　nonaffine　dynamics.　First,　for　two　controllers　in　nonzero-sum　games,　we　adopt　different　boundaries　to　constrain　them,　which　ensures　their　independence.　Then,　the　specific　derivation　process　of　the　proposed　algorithm　is　given　by　using　the　DHP　technique.　Meanwhile,　an　appropriate　triggering　condition　is　established　to　decrease　the　amount　of　computation.　Finally,　a　simulation　example　is　carried　out　to　demonstrate　the　applicability　of　the　constructed　method.　The　event-based　constrained　control　algorithm　is　able　to　substantially　reduce　the　updating　times　of　the　control　input,　while　still　maintaining　an　impressive　performance.　©　2021　ACM.