Integrating Artificial Intelligence into Decision Theory Models: Enhancing Accuracy and Efficiency in Decision -Making

Integrating Artificial Intelligence (AI) into decision theory models represents a significant step forward in improving how we make decisions. In this article, we take a closer look at how AI can be systematically woven into four well-known decision-making models: Decision Trees, Multi-Criteria Decision Analysis (MCDA), and Linear Programming (LP). By tapping into the predictive capabilities of machine learning, the flexibility of AI algorithms, and the analytical power of big data, organizations can greatly enhance their decision-making processes. AI helps with processing data in real time, managing changing constraints, and understanding complex relationships between variables, leading to insights that were once out of reach. Through practical examples and methodologies, we show how AI can refine each decision model, ultimately resulting in smarter decisions and improved performance for organizations. This exploration highlights the importance for modern businesses to adopt AI within traditional decision-making frameworks, paving the way for more agile and effective decision-making in a rapidly changing world.

کلیدواژه ها:

Decision Theory ، Model ، Integrating ، Artificial Intelligence