Optimization Theory
The study of finding the best solution from a set of feasible solutions.
The study of finding the best solution from a set of feasible solutions.
The use of data, algorithms, and machine learning to recommend actions that can achieve desired outcomes.
A cognitive bias that causes people to believe they are less likely to experience negative events and more likely to experience positive events than others.
The process of continuously improving a product's performance, usability, and value through data-driven decisions and iterative enhancements.
A decision-making rule where individuals choose the option with the highest perceived value based on the first good reason that comes to mind, ignoring other information.
The practice of using data analytics and metrics to make informed decisions, focusing on measurable outcomes and efficiency rather than intuition or traditional methods.
A concept that humans make decisions within the limits of their knowledge, cognitive capacity, and available time, leading to satisficing rather than optimal solutions.
The compromises made between different design options, balancing various factors like usability, aesthetics, and functionality.
Pre-set options in a system that are designed to benefit users by simplifying decisions and guiding them towards the best choices.