Digitalizing tabletop games for general game playing(GGP) AI research is a continuously growing field. TabletopGames Framework (TAG) is a framework developed to simplifythe process of implementing tabletop board games to digital form.Sushi Go! is a game that combines simultaneous action selectionand complete information. This creates a unique combination ofmechanics, which presents a new challenge for GGP agents. Byimplementing Sushi Go! into TAG, we can test different agent’sperformance using these mechanics and compare them to theirexisting performances in the other games of TAG. Results ofthis testing are presented, which display that the framework iscapable of implementing Sushi Go! and that the agents performwith mixed results. Further developing heuristics for the agentsshould prove to increase their performance when faced with thesetypes of games.