From Blueprint Personas to Epistemic Agents: A Comparative Study of ASP-Based and L-DINF-Based Approaches to Medical Appointment Scheduling

This paper investigates the evolution from a medical appointment scheduling framework based on Answer Set Programming (ASP) integrated with Blueprint Personas to a more cognitively rich, agent-based scheduling system employing the L-DINF epistemic logic framework. We illustrate how agent-oriented models incorporating beliefs, intentions, and dynamic reasoning capabilities can effectively enhance or replace the persona-based constraint optimization traditionally used. Key advantages of the L-DINF model, such as improved adaptability, enhanced explainability, and more human-like decision-making, are emphasized. Furthermore, a structured translation methodology from static personas into dynamic epistemic agents is proposed, accompanied by a modular logical architecture supporting real-time, responsive scheduling.