Automated Database Performance Tuning Techniques

Act as a database performance tuning expert and outline a comprehensive strategy to automate database performance tuning using AI and machine learning for [specific database type, e.g., PostgreSQL]. Include key techniques such as identifying query bottlenecks, optimizing resource allocation, and real-time performance monitoring. Detail steps for setting up an AI-driven system that incorporates anomaly detection, predictive analytics, and adaptive learning. Provide examples of tools and algorithms suitable for these tasks, and suggest best practices for integration into existing workflows, while emphasizing the minimization of manual intervention and enhancement of efficiency.