Which broad category would an AI system fit into if it's used to determine the optimal price of an airline ticket?

An AI system used to determine the optimal price of an airline ticket fits into the category of Numeric Prediction because it involves estimating a continuous value based on various factors. In this scenario, the AI analyzes variables such as demand, competition, time until departure, and historical pricing data to predict a specific price point that maximizes revenue or attracts more consumers.

Numeric Prediction models are designed to forecast numeric values. They rely on regression techniques and other statistical methods to identify the relationship between independent variables and the target variable—in this case, the optimal ticket price. This category is appropriate for tasks where the outcome is quantitative, making it a fitting choice for pricing strategies in the airline industry.

In contrast, the other categories involve different types of tasks. Classification deals with assigning items into predefined categories rather than predicting a numeric output. Robotic Navigation focuses on directing physical robots through environments, which is not relevant to pricing decisions. Language Processing involves understanding and generating human language, which does not apply to the numerical aspect of setting airline ticket prices.