Artificial Intelligence Programming 2025 – 400 Free Practice Questions to Pass the Exam

The scenario where the actions of one player affect the utility of another is best described as a game. In game theory, which studies strategic interactions between multiple players, the outcome for each participant depends not only on their own decisions but also on the decisions made by others. This interaction introduces various dynamics, such as cooperation, competition, and negotiation, where the payoffs or utilities can change dramatically based on the choices of other players.

This concept illustrates the interdependence of decisions in a multi-agent environment, making it a crucial aspect in fields such as economics, political science, and artificial intelligence. In contrast, the other options represent different concepts. Decision theory typically focuses on individual decision-making processes rather than interactions between players. Utility pertains to the satisfaction or payoff received but does not inherently involve interaction with other players. A Markov Decision Process is a mathematical framework used for modeling decision-making in situations where outcomes are partly random and partly under the control of a decision-maker, often in single-agent contexts rather than those involving multiple competitive agents.