Intelligent Agents Questions and Answers

Q: How is risk aversion represented in a utility framework?

A concave utility means that each additional unit of money or reward is worth less than the last, so a certain amount is preferred to a gamble of the same expected value. That is how risk attitude enters without abandoning expected utility maximisation. Distorting probabilities, adding penalties and refusing uncertainty are ad hoc alternatives that lack the axiomatic justification. Absorbing an apparent departure from the theory into the shape of the utility function keeps the framework intact.

Q: What is the role of the critic in a learning agent?

The critic observes the percepts and reports performance against a fixed external standard, since the agent's own utility function cannot be used to judge whether that utility function is right. Without an external standard the agent could improve its score by changing its opinion of what counts. Architecture, algorithm selection and exploration belong elsewhere. Requiring the feedback to come from outside the system being improved is what makes the learning meaningful.

Q: Why must the critic's standard be external to the agent?

If the agent could modify the criterion by which it is judged, improvement would become trivial and meaningless, so the standard must be fixed and outside its control. This is the same reason a performance measure is set by the designer rather than by the agent. Accuracy, access and regulation are secondary. A feedback loop in which the system can alter its own target is not a learning loop at all, which is a point that applies well beyond agent design.

Q: Consider the following statements about agent architectures. 1. A simple reflex agent uses only the current percept 2. A model based agent maintains internal state 3. A utility based agent cannot handle conflicting goals Which of the statements given above is or are correct?

The first two are correct. Handling conflicting goals is precisely what a utility function is for, since it converts incomparable objectives into a single ranking. A goal based agent is the one that cannot resolve conflicts, having only a binary criterion. The three statements together trace the ladder of architectures, and the third inverts the very capability that motivates the last rung.

Q: Consider the following pairings of representation and capability. Atomic - states compared only for equality Factored - states described by variables Structured - objects and relations between them Atomic - constraint propagation between variables How many of the pairs given above are correctly matched?

The first three are correct. Constraint propagation requires variables to propagate between, so it needs a factored representation at least, and an atomic representation supports only equality tests. The hierarchy matters because each level admits a class of algorithm the level below cannot express, so choosing a representation commits the design to a set of available techniques before any of them is selected.

Q: What is an agent's action space?

The action space is what the agent can do, and its size and structure determine how hard action selection is: a discrete space of a few options admits exhaustive comparison, while a continuous space requires optimisation. The reachable states are a consequence of the actions rather than the actions themselves. Space and time are separate constraints. Characterising both the percept and the action spaces is part of specifying a task before any design begins.

41.

How is risk aversion represented in a utility framework?

A.By a utility function that is concave in the quantity of interest
B.By reducing every probability estimate towards one half
C.By adding a penalty term to the expected utility calculation
D.By refusing any action whose outcome is not certain

Answer: A

A concave utility means that each additional unit of money or reward is worth less than the last, so a certain amount is preferred to a gamble of the same expected value. That is how risk attitude enters without abandoning expected utility maximisation. Distorting probabilities, adding penalties and refusing uncertainty are ad hoc alternatives that lack the axiomatic justification. Absorbing an apparent departure from the theory into the shape of the utility function keeps the framework intact.

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42.

What is the role of the critic in a learning agent?

A.Generating exploratory actions so as to gather new experience
B.Telling the learning element how well the agent is doing
C.Criticising the design of the agent's architecture
D.Selecting which of several learning algorithms to apply

Answer: B

The critic observes the percepts and reports performance against a fixed external standard, since the agent's own utility function cannot be used to judge whether that utility function is right. Without an external standard the agent could improve its score by changing its opinion of what counts. Architecture, algorithm selection and exploration belong elsewhere. Requiring the feedback to come from outside the system being improved is what makes the learning meaningful.

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43.

Why must the critic's standard be external to the agent?

A.The agent has no access to its own internal performance measure
B.Regulations require an independent assessment of agent behaviour
C.Otherwise the agent could improve its score by changing the standard
D.External standards are more accurate than internal ones

Answer: C

If the agent could modify the criterion by which it is judged, improvement would become trivial and meaningless, so the standard must be fixed and outside its control. This is the same reason a performance measure is set by the designer rather than by the agent. Accuracy, access and regulation are secondary. A feedback loop in which the system can alter its own target is not a learning loop at all, which is a point that applies well beyond agent design.

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44.

Consider the following statements about agent architectures.

1. A simple reflex agent uses only the current percept

2. A model based agent maintains internal state

3. A utility based agent cannot handle conflicting goals

Which of the statements given above is or are correct?

A.1 and 3 only
B.2 and 3 only
C.1, 2 and 3
D.1 and 2 only

Answer: D

The first two are correct. Handling conflicting goals is precisely what a utility function is for, since it converts incomparable objectives into a single ranking. A goal based agent is the one that cannot resolve conflicts, having only a binary criterion. The three statements together trace the ladder of architectures, and the third inverts the very capability that motivates the last rung.

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45.

Match each environment property with the capability it demands.

List I

A. Partially observable

B. Stochastic

C. Dynamic

D. Multi-agent

List II

P. internal state

Q. reasoning about probability

R. real time response

S. strategic reasoning

Select the correct match.

A.A-P, B-Q, C-R, D-S
B.A-Q, B-P, C-S, D-R
C.A-R, B-S, C-P, D-Q
D.A-P, B-R, C-Q, D-S

Answer: A

Each dimension of the environment taxonomy selects a different capability, which is exactly why the classification is worth doing before any design work begins. Memory, probability, timeliness and strategy are four distinct requirements, and a task at the difficult end of every dimension needs all four. Driving is the standard example of exactly that, which is why it has proved so much harder than the early demonstrations suggested.

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46.

Consider the following pairings of representation and capability.

Atomic - states compared only for equality

Factored - states described by variables

Structured - objects and relations between them

Atomic - constraint propagation between variables

How many of the pairs given above are correctly matched?

A.All four
B.Only three
C.Only one
D.Only two

Answer: B

The first three are correct. Constraint propagation requires variables to propagate between, so it needs a factored representation at least, and an atomic representation supports only equality tests. The hierarchy matters because each level admits a class of algorithm the level below cannot express, so choosing a representation commits the design to a set of available techniques before any of them is selected.

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47.

Three of the following are dimensions of the standard environment classification. Which is the odd one out?

Symbolic or connectionist

Fully or partially observable

Deterministic or stochastic

Episodic or sequential

A.Deterministic or stochastic
B.Episodic or sequential
C.Symbolic or connectionist
D.Fully or partially observable

Answer: C

Observability, determinism and episodicity are properties of the task environment and are settled by the problem rather than the designer. Symbolic against connectionist is a choice of method, made by the designer in response to the environment. Keeping the properties of the problem separate from the choices about the solution is the discipline the classification exists to enforce, and confusing the two leads to designs justified by preference rather than by the task.

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48.

Assertion (A): An agent in a partially observable environment needs internal state.

Reason (R): The current percept alone may not distinguish situations requiring different actions.

Select the correct answer from the options below.

A.Both A and R are true, but R is not the correct explanation of A
B.A is true but R is false
C.A is false but R is true
D.Both A and R are true, and R is the correct explanation of A

Answer: D

Both are true and the second is the reason for the first. If two states look identical to the sensors but demand different responses, no function of the current percept can be correct in both, so a memory of earlier percepts is logically necessary. It is an argument from impossibility rather than from efficiency, which makes it much stronger. Establishing that an architecture cannot work, rather than that it works badly, settles the design question immediately.

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49.

Statement I: A reflex agent can perform well in a fully observable environment.

Statement II: A reflex agent can perform well in a partially observable environment.

In the light of the above statements, choose the correct answer.

A.Statement I is correct but Statement II is incorrect
B.Both Statement I and Statement II are correct
C.Both Statement I and Statement II are incorrect
D.Statement I is incorrect but Statement II is correct

Answer: A

The first is correct: where the percept reveals the whole state, a condition action rule can always be correct. The second fails because the same percept may arise in states requiring different actions, and no rule keyed on the percept alone can be right in both. The pair shows that architecture adequacy is a property of the architecture and the environment together rather than of the architecture alone, which is the central lesson of the whole classification.

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50.

What is an agent's action space?

A.The time available to the agent before it must act
B.The set of actions available to it at a given moment
C.The physical region within which the agent may operate
D.The set of states the agent's actions can bring about

Answer: B

The action space is what the agent can do, and its size and structure determine how hard action selection is: a discrete space of a few options admits exhaustive comparison, while a continuous space requires optimisation. The reachable states are a consequence of the actions rather than the actions themselves. Space and time are separate constraints. Characterising both the percept and the action spaces is part of specifying a task before any design begins.

Discuss in Forum

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