Artificial Intelligence Foundations and Intelligent Agents Syllabus

Foundations and Intelligent Agents syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Foundations and Intelligent Agents in Artificial Intelligence, not a summary of it.

1. 1

   Introduction to AI

   4 topics

   • What is Artificial Intelligence
   • Foundations of AI
   • History of AI
   • State of the Art and Applications
2. 2

   Intelligent Agents

   4 topics

   • Agents and Environments
   • Nature of Environments
   • Structure of Agents
   • Representing Agent State
3. 3

   Problem Solving by Search

   3 topics

   • Problem-Solving Agents
   • Example Problems
   • Searching for Solutions

Foundations and Intelligent Agents flashcards for Artificial Intelligence

20 of 50 cards from the Foundations and Intelligent Agents deck — real questions with worked answers.

1. What is the standard definition of Artificial Intelligence used in Russell & Norvig, organized along two dimensions?

   AI is defined along two dimensions: (1) thinking vs. behaving, and (2) fidelity to human performance vs. an ideal standard of rationality. This yields four approaches: thinking humanly, thinking rationally, acting humanly, and acting rationally (the last is the modern focus).

2. List the four categories of AI definitions in the 'humanly vs. rationally' / 'thought vs. behavior' grid.

   1) Acting humanly (Turing Test approach), 2) Thinking humanly (cognitive modeling), 3) Thinking rationally (laws of thought / logic), 4) Acting rationally (rational agent approach).

3. What is the Turing Test, and what capabilities must a machine possess to pass it?

   Proposed by Alan Turing (1950), a computer passes if a human interrogator cannot reliably distinguish it from a human via written responses. It requires natural language processing, knowledge representation, automated reasoning, and machine learning.

4. What additional capabilities does the Total Turing Test require beyond the standard Turing Test?

   The Total Turing Test adds a video signal and a physical hatch to pass objects, requiring computer vision (to perceive objects) and robotics (to manipulate objects and move about).

5. Define a rational agent in the 'acting rationally' approach to AI.

   A rational agent is one that acts so as to achieve the best outcome, or, under uncertainty, the best expected outcome — it does the 'right thing' given what it knows to maximize its performance measure.

6. Name the six major foundational disciplines that contributed to AI.

   Philosophy, Mathematics, Economics, Neuroscience, Psychology, Computer engineering (also Control theory/cybernetics and Linguistics).

7. Which three foundational questions did Mathematics contribute to AI?

   Logic (formal rules for valid conclusions), Computation (what can be computed / decidability, e.g., Church-Turing), and Probability (reasoning with uncertain information).

8. What did Economics contribute to AI in terms of decision-making?

   Utility theory (formalizing preferences and payoffs), decision theory (combining probability + utility), and game theory — providing the framework for how agents should make decisions to maximize expected utility.

9. In what year and at what event was the term 'Artificial Intelligence' coined, and by whom?

   At the Dartmouth Workshop in 1956; the term 'Artificial Intelligence' was proposed by John McCarthy.

10. What was the significance of the program 'Logic Theorist' (1955-56) by Newell and Simon?

    It was one of the first AI programs; it could prove theorems from Russell & Whitehead's Principia Mathematica, demonstrating that machines could perform reasoning previously thought to require human intelligence.

11. What period is known as the first 'AI Winter,' and what triggered it?

    The mid-1970s (roughly 1974 onward). It was triggered by unmet expectations, the intractability (combinatorial explosion) of early methods, and reports like the Lighthill report cutting funding.

12. What were 'expert systems,' and which era did they dominate?

    Rule-based systems encoding domain knowledge as if-then rules (e.g., MYCIN, DENDRAL), dominating the 1980s and creating the first commercial AI industry.

13. What is meant by 'AI becomes a science' in the 1990s?

    AI shifted toward rigorous methods based on probability theory, decision theory, and statistics, with hypotheses tested empirically — moving away from ad-hoc approaches toward mathematically grounded, reproducible methods.

14. Name three landmark milestones demonstrating the state of the art in AI.

    Deep Blue defeating Garry Kasparov at chess (1997), IBM Watson winning Jeopardy! (2011), and DeepMind's AlphaGo defeating Lee Sedol at Go (2016); more recently large language models and deep learning.

15. Define an agent in the context of AI.

    An agent is anything that perceives its environment through sensors and acts upon that environment through actuators.

16. Define percept and percept sequence.

    A percept is the agent's perceptual input at any given instant. A percept sequence is the complete history of everything the agent has ever perceived.

17. What is an agent function, and how does it relate to an agent program?

    The agent function is an abstract mathematical mapping from any given percept sequence to an action: $f: \mathcal{P}^{*} \to \mathcal{A}$. The agent program is the concrete implementation of that function running on the agent's architecture.

18. Give the equation relating an agent's overall structure.

    $$\text{agent} = \text{architecture} + \text{program}$$ where the architecture is the physical computing device with sensors/actuators, and the program implements the agent function.

19. Define a performance measure and explain why it belongs in the environment, not the agent.

    A performance measure is an objective criterion for evaluating the success of an agent's behavior. It is designed according to what one actually wants in the environment (the effects on the environment), rather than how one thinks the agent should behave.

20. State the formal definition of a rational agent in terms of the performance measure.

    For each possible percept sequence, a rational agent selects an action expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has.

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