Example Concept: Autonomous AI agents use sensors and data inputs to continuously monitor their environment. When an unexpected change is detected, such as an obstacle appearing in a robot's path, the agent processes this information using its onboard algorithms. It then updates its decision-making model, often employing techniques like reinforcement learning or rule-based adjustments, to choose a new course of action that avoids the obstacle while still aiming to achieve its primary goal.