In　this　article,　a　decentralized　event-triggered　control　(ETC)　strategy　is　developed　for　nonlinear　large-scale　systems　subjects　to　matched　interconnections.　First,　the　large-scale　interconnected　systems　are　transformed　to　several　nominal　isolated　subsystems.　Then,　the　optimal　control　problem　of　nominal　isolated　subsystems　is　solved　via　an　event-triggered　method　based　on　adaptive　critic　learning.　Note　that　the　ETC　scheme　is　adopted　to　reduce　the　computational　burden　and　communication　resources.　Moreover,　a　single　network　adaptive　critic　structure　is　constructed　to　approximate　the　optimal　cost　and　the　control　policy.　By　employing　a　stabilizing　term　in　the　weight　updating　law　of　the　critic　neural　network,　there　is　no　requirement　for　adopting　initial　admissible　control　in　the　proposed　algorithm.　Furthermore,　we　use　the　Lyapunov　method　to　demonstrate　that　estimated　weight　vectors　used　in　the　critic　networks　are　uniformly　ultimately　bounded.　Finally,　we　provide　an　example　to　validate　the　proposed　decentralized　event-triggered　control　strategy.