Dynamic Pricing Strategy Optimization Model

Develop a sophisticated dynamic pricing optimization model that uses reinforcement learning techniques to maximize revenue across different product categories. Create a simulation environment that can model complex pricing interactions, competitor responses, and customer price sensitivity. Implement a multi-armed bandit algorithm with Thompson sampling that can adaptively adjust pricing strategies in near-real-time while providing explainable decision-making rationales.