We present a hybrid framework that combines Answer Set Programming (ASP) for baseline schedule generation with L-DINF for local, explainable adaptation under disruptions. The key technical contribution is a compilation from relevant ASP scheduling artifacts to L-DINF beliefs, intentions, feasibility conditions, and preferences. This allows agents to perform bounded local repair and inter-group delegation when the baseline schedule becomes infeasible, while preserving a fallback to ASP re-optimization for non-local changes. We present a proof-of-concept executable realization in DALI, an agent-oriented logic programming language, for the L-DINF fragment, validated through an execution trace on SICStus Prolog. The proposal is discussed on a healthcare proof-of-concept and positioned as a logic-based architecture for combining global constraint solving with local epistemic adaptation.