The AGWM (Affordance-Grounded World Model) introduces a new approach to model-based learning by tracking dynamic action executability in interactive environments, addressing limitations of traditional world models. This innovation shows promise in reducing prediction errors and enhancing generalization in simulated environments, potentially benefiting AI development in complex systems.