A new framework called Multi-Objective Constraint Inference (MOCI) has been introduced to enhance reinforcement learning by effectively modeling diverse expert behaviors and preferences. MOCI outperforms existing methods in predictive performance while maintaining computational efficiency, making it a promising tool for real-world applications in constraint inference and preference learning.