Review AI Exam 1

[Lisp] What is the parenthesis notation for this cons cell structure?

((BOWS ARROWS) (FLOWERS CHOCOLATES))

[Lisp] Given (setf line '(roses are red)) What is the result of: (cons (last line) line)

((red) roses are red)

[Lisp] What is the result of (mapcar #'try '(1 3 5)) where the function try is defined as follows: (defun try (n) (+ 2 n))

(3 5 7)

[Lisp] What is the parenthesis notation for this cons cell structure? ** -> ** -> ** -> NIL | | | V V V RED GREEN BLUE

(RED GREEN BLUE)

[Lisp] What is CADR of the following expression? ((BLUE CUBE) (RED PYRAMID))

(RED PYRAMID)

[Lisp] What is the result of: (list 'cons t nil)

(cons t nil)

[Lisp] What is the lambda function to subtract 7 from a number?

(lambda (n) (- n 7))

[Lisp] What is the result of: (mapcar #'zerop '(2 0 -5))

(nil t nil)

[Lisp] What is the result of: (eval nil)

(nil)

[Lisp] What is the result of: (eval (list 'cons t nil))

(t)

[Lisp] What is the result of the following Lisp function? (length '((1 2 3) (4 5 6) (7 8 9) (10 11 12)))

4

[Lisp] What is the result of the following Lisp function? (length '((ONE) FOR ALL (AND (TWO (FOR ME)))))

4

[Lisp] What is the result of the following Lisp function? (length '(1 2 3 4))

4

[Lisp] What is the result of (+ 1 2 3)

6

[Lisp] What is the result of: (+ (- 5 2) 3)

6

Consider the following 8-puzzle configuration of the start state and the goal state. 7 2 4 | * 1 2 5 * 6 | 3 4 5 8 3 1 | 6 7 8 Using a heuristic h1 (number of tiles in wrong position), What is the h1(start-state)?

8

Select the best choice for the following question. Consider the cost functions for a node n as follows: g(n) - the cost to reach the node (from the start) h(n) - the cost to get from the node to the goal (often an estimate). f(n) - an evaluation function which is the sum of g(n) and h(n) ____ is identical to UNIFORM COST SEARCH except that this uses f(n) = g(n) + h(n), instead of f(n) = g(n).

A*

Select the best choice for the following question. Consider the cost functions for a node n as follows: g(n) - the cost to reach the node (from the start) h(n) - the cost to get from the node to the goal (often an estimate). f(n) - an evaluation function which is the sum of g(n) and h(n) ____ search strategy evaluates nodes with the cost function f(n) by combining g(n) and h(n) where h(n) is never overestimated.

A*

In the game tree show below, the first level is a MAX level, the second is a MIN level, the third is a MAX level and the fourth is a MIN level. Each leaf-node shows its value for MiniMax search, and each node is labeled (from left to right) as L1, L2, ... Apply alpha-beta search to the tree. Some leaves need not be evaluated (to be pruned). After processing all the nodes below, what would be the alpha value or beta value of the node (that is, the parent of L1 and L2) shown below for alpha and beta values?

Alpha is negative infinity

In the game tree show below, the first level is a MAX level, the second is a MIN level, the third is a MAX level and the fourth is a MIN level. Each leaf-node shows its value for MiniMax search, and each node is labeled (from left to right) as L1, L2, ... Apply alpha-beta search to the tree. Some leaves need not be evaluated (to be pruned). After processing all the nodes below, what would be the alpha value or beta value of the node (that is, the parent of L1 and L8) shown below for alpha and beta values?

Alpha is negative infinity

In the game tree show below, the first level is a MAX level, the second is a MIN level, the third is a MAX level and the fourth is a MIN level. Each leaf-node shows its value for MiniMax search, and each node is labeled (from left to right) as L1, L2, ... Apply alpha-beta search to the tree. Some leaves need not be evaluated (to be pruned). After processing all the nodes below, what would be the alpha value or beta value of the node (that is, the parent of L1 to L4) shown below for alpha and beta values?

Beta is positive infinity

The majority of work in the area of search has gone into finding the right search strategy for a problem. In our study of the field we will evaluate strategies in terms of four criteria. Select the best choice for each criteria. Is the strategy guaranteed to find a solution when there is one?

Completeness

The majority of work in the area of search has gone into finding the right search strategy for a problem. Select the best choice for each question. The drawback of ______ is that it can get stuck going down the wrong path.

Depth-first search

The majority of work in the area of search has gone into finding the right search strategy for a problem. Select the best choice for each question. ______ always expands one of the nodes at the deepest level of the tree. Only when the search hits a dead end (a nongoal node with no expansion) does the search go back and expand nodes at shallower levels.

Depth-first search

The majority of work in the area of search has gone into finding the right search strategy for a problem. Select the best choice for each question. ______ needs to store only a single path from the root to a leaf node, along with the remaining unexpanded sibling nodes for each node on the path.

Depth-first search

Depth-Limited search is Optimal.

False

The majority of work in the area of search has gone into finding the right search strategy for a problem. Select the best choice for each question. Strategies called informed search strategies are also called ___.

Heuristic Search

______ is a peak that is higher than each of its neighboring states but lower than the global maximum.

Local Maximum

_______ is a flat area of the state-space landscape. It can be a flat local maximum, from which no uphill exit exists, or a shoulder, from which progress is possible.

Plateau

______ hill climbing conducts a series of hill-climbing searches from randomly generated initial states, until a goal is found.

Random-Restart

______ hill climbing chooses at random from among the uphill moves; the probability of selection can vary with the steepness of the uphill move.

Stochastic

Breadth-First search is Complete.

True

Breadth-First search is Optimal.

True

Iterative-Deepening search is Complete.

True

The majority of work in the area of search has gone into finding the right search strategy for a problem. Select the best choice for each question. ______ modifies the breadth-first strategy by always expanding the lowest-cost node on the fringe (as measured by the path cost g(n)), rather than the lowest-depth node.

Uniform cost search

The majority of work in the area of search has gone into finding the right search strategy for a problem. Select the best choice for each question. This term ______ means that they have no information about the number of steps or the path cost from the current state to the goal - all they can do is distinguish a goal state from a nongoal state.

Uninformed Search

The Turing Test measures intelligence as

a human's inability to detect a machine's presence

An agent performs

actions

A rational agent

acts as well as possible

A reflex agent

acts only on current percept

A(n) _____ heuristic never overestimates the cost to reach the goal, i.e., it is optimal.

admissible

Consider the following 8-puzzle configuration of the start state and the goal state. 7 2 4 | * 1 2 5 * 6 | 3 4 5 8 3 1 | 6 7 8 Using a heuristic h1 (number of tiles in wrong position), h1 is

admissible

If heuristic h(n) is ______, A* using TREE-SEARCH is optimal.

admissible

Select the best choice for the following question. Consider the cost functions for a node n as follows: g(n) - the cost to reach the node (from the start) h(n) - the cost to get from the node to the goal (often an estimate). f(n) - an evaluation function which is the sum of g(n) and h(n) If h(n) is ___, then the values of f(n)=g(n)+h(n) along any path are nondecreasing.

admissible

Select the best choice for the following question. Consider the cost functions for a node n as follows: g(n) - the cost to reach the node (from the start) h(n) - the cost to get from the node to the goal (often an estimate). f(n) - an evaluation function which is the sum of g(n) and h(n) Using Straight-line distance for h(n) in Romanian routing problem is ___ because the shortest path between any two points is a straight line.

admissible

Select the best choice for the following question. Consider the cost functions for a node n as follows: g(n) - the cost to reach the node (from the start) h(n) - the cost to get from the node to the goal (often an estimate). f(n) - an evaluation function which is the sum of g(n) and h(n) h(n) which is ___ is one that never overestimates the cost to reach the goal.

admissible

Minimax is a

algorithm

[Lisp] Given (setf line '(roses are red)) What is the result of: (nth 1 line)

are

An agent is

autonomous and situated in an environment

Consider Time and space complexity which are measured in terms of b: maximum branching factor of the search tree d: depth of the least-cost solution m : maximum depth of the state space (may be infinite) l (letter L): is the depth limit. Note: C* is the cost of the optimal solution path. Select the best answer for each question. The Space complexity of Uniform-Cost search is _____.

b to the power of (1+⌊C*/ε⌋)

Consider Time and space complexity which are measured in terms of b: maximum branching factor of the search tree d: depth of the least-cost solution m : maximum depth of the state space (may be infinite) l (letter L): is the depth limit. Note: C* is the cost of the optimal solution path. Select the best answer for each question. The time complexity of Uniform-Cost search is _____.

b to the power of (1+⌊C*/ε⌋)

Consider Time and space complexity which are measured in terms of b: maximum branching factor of the search tree d: depth of the least-cost solution m : maximum depth of the state space (may be infinite) l (letter L): is the depth limit. Note: C* is the cost of the optimal solution path. Select the best answer for each question. The Space complexity of Breadth-First search is _____.

b^d (b to the power of d)

Consider Time and space complexity which are measured in terms of b: maximum branching factor of the search tree d: depth of the least-cost solution m : maximum depth of the state space (may be infinite) l (letter L): is the depth limit. Note: C* is the cost of the optimal solution path. Select the best answer for each question. The time complexity of Breadth-First search is _____.

b^d (b to the power of d)

Hill climbing is a(n)

best-first search

AI problems tend to involve

combinatorial explosion of running time

A heuristic h is ______ if for every node n, every successor n' of n generated by any action a (preserving order - triangular inequality - monotonic), h(n) ≤ c(n, a, n') + h(n')

consistent

If a heuristic h is ______, then A* using GRAPH-SEARCH is optimal.

consistent

If a heuristic h is ______, then f(n) is non-decreasing along any path.

consistent

Select the best choice for the following question. Consider the cost functions for a node n as follows: g(n) - the cost to reach the node (from the start) h(n) - the cost to get from the node to the goal (often an estimate). f(n) - an evaluation function which is the sum of g(n) and h(n) This ___ condition for h(n) in A* is also called sometimes monotonicity for it preserves triangular inequality.

consistent

An optimization problem finds a maximum or minimum value that satisfies a certain

constraint

Optimizing search compares

costs of paths

The easiest environment below is

deterministic, static, fully observable

The most difficult environment below is

dynamic and partially observable

Rationality maximizes ______ whereas perfection maximizes actual performance.

expected performance

Combinatorial explosion is

exponential size of state space

One well-known strategy for state-space search is called

generate and test

[Alpha-Beta Pruning] For the game-tree shown below, state for which values of x the dashed branch with the scissors will be pruned. If the pruning will not happen for any value of x, then it should be "none". If pruning will happen for all values of x, select "all".

greater than or equal to 3

A rule of thumb that guides state-space search is a(n)

heuristic

Admissibility, informedness, and monotonicity are features of all

heuristics

[Alpha-Beta Pruning] For the game-tree shown below, state for which values of x the dashed branch with the scissors will be pruned. If the pruning will not happen for any value of x, then it should be "none". If pruning will happen for all values of x, select "all". (Note: Δ is Maximizer, ∇ is Minimizer)

less than or equal to 1

[Lisp] What is the result of the following expression: (eq '(a b) '(a b))

nil

[Lisp] What is the result of the following expression: (eql 3 3.0)

nil

[Lisp] What is the result of: (eval (list 'eval nil))

nil

A problem of finding a set of values that yields the highest or lowest return value when used as parameters to a function is

optimization

An agent receives _______ from the environment.

percepts

Newell and Simon hypothesized that a necessary and sufficient condition for intelligence is

rationality

[Lisp] Given (setf line '(roses are red)) What is the result of: (first (last line))

red

Local search

reduces difficulty of some hard problems

Utility-based agents seek mainly

reward

A goal is a(n)

set of states

A set of possible arrangements of values is a(n)

state-space

Games and puzzles are simple examples of

state-space search

The most difficult environment below is

stochastic, dynamic, partially observable

[Lisp] What is the result of the following expression: (equal '(a b) '(a b))

t

A drawback of hill climbing is

tendency to become stuck at local maxima

A well-known way to define machine intelligence is

the Turing Test

The assumption that a game opponent will make the best possible move is made in

the minimax algorithm

The breadth-first search

uses a queue

The depth-first search

uses a stack