1. Despite their wide application, intelligent systems face several key challenges, including:

2. Uncertainty: Physical sensors and effectors often provide limited, noisy, or inaccurate data and actions. As a result, some system decisions or actions may be imprecise due to sensor noise or execution limitations.

3. Dynamic World: Real-world environments change continuously. Intelligent systems must therefore make decisions quickly to adapt to these changes in real time.

4. Time-Consuming Computation: Finding an optimal path or solution often requires extensive searching within a large problem space, which is computationally expensive. During this computation, the environment may change, making the computed solution outdated or ineffective.

5. Mapping and Perception: Significant information can be lost when transforming a three-dimensional world into a two-dimensional representation. Computer vision systems must handle challenges such as changes in perspective, background clutter, motion, lighting variations, scale differences, and variations within and between object classes.