AI Fundamentals Advanced Quiz 1
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Advanced Quiz 1
1. Which of the following best describes the "frame problem" in AI?
The challenge of representing and updating knowledge about a dynamic world as actions are taken
The difficulty of drawing frames in computer graphics
A problem with displaying images on monitors
2. What is the main idea behind the "Chinese Room" argument by John Searle?
A system can appear to understand language without true comprehension or consciousness
AI systems can learn Chinese faster than humans
AI systems can only process numbers, not language
3. Which of these is a key limitation of symbolic AI approaches?
Difficulty handling perception and learning from raw sensory data
They require neural networks
They are only used for playing games
4. What is a Markov Decision Process (MDP) used for in AI?
Modeling decision making in environments with stochastic outcomes
Image recognition
Sorting data efficiently
5. Which of these is a primary purpose of ontologies in AI?
To formally define the relationships and categories within a domain of knowledge
To speed up computation
To generate random numbers
6. What is the "no free lunch" theorem in AI and optimization?
No single algorithm is best for all possible problems
AI systems require a lot of data
There is no such thing as free software
7. Which of the following is a challenge for explainable AI (XAI)?
Making complex model decisions understandable to humans without sacrificing performance
Translating languages automatically
Improving battery life
8. What is the difference between deductive and inductive reasoning in AI?
Deductive reasoning applies general rules to specific cases; inductive reasoning infers general rules from specific cases
Deductive reasoning is only used by humans
Inductive reasoning is always more accurate
9. Which of these is a feature of a blackboard architecture in AI?
Multiple specialized subsystems (knowledge sources) collaborate via a shared workspace
All knowledge is stored in a single file
It is used only for drawing
10. What is the main function of a utility-based agent?
To select actions that maximize expected utility based on preferences and probabilities
To always choose random actions
To minimize the use of electricity
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