In the context of artificial intelligence and economics, a utility function is a mathematical representation that quantifies an agent's preferences and satisfaction derived from various outcomes or choices. Utility functions play a crucial role in decision-making processes, helping agents evaluate the desirability of different actions based on their goals and values. In reinforcement learning, agents use utility functions to assess the expected rewards associated with specific actions in given states, guiding their choices to maximize cumulative rewards. By modeling preferences and trade-offs, utility functions enable AI systems to make rational and informed decisions, closely aligning with human behavior and economic theory.