Agent-Based Modeling (ABM) is a computational modeling approach that simulates the interactions of autonomous agents in a defined environment. Each agent operates based on a set of rules and can adapt its behavior based on interactions with other agents and the environment. ABM is particularly useful for understanding complex systems where individual behaviors lead to emergent phenomena. Common applications include social sciences, ecology, economics, and epidemiology, where it helps in predicting outcomes and exploring scenarios that are difficult to analyze using traditional methods.
A/B testing compares two versions of a product to optimize performance and improve user engagement.
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AI Fundamentals