👉 Policy computing is a framework that integrates policy-based approaches with machine learning and decision-making techniques to automate and optimize complex systems. It involves defining policies—rules or guidelines that dictate system behavior—often derived from expert knowledge, data, or learned patterns. These policies are then implemented using algorithms that can adapt and evolve over time, learning from new data to refine their decisions. This approach is particularly useful in dynamic environments where static rules are insufficient, enabling systems to handle uncertainty and complexity more effectively. By combining the interpretability of rule-based systems with the adaptability of machine learning, policy computing facilitates smarter, more responsive decision-making across various domains, from autonomous vehicles to smart grids and healthcare.
