AI exam 1
Using a heuristic H2 (the sum of Manhattan distances of all tiles from their goal positions), H2 for start-state is initially _____. https://elearning.utdallas.edu/bbcswebdav/pid-5336513-dt-content-rid-124019696_1/xid-124019696_1
18
[game-tree] 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 L3 and L4) shown below for alpha and beta values? https://elearning.utdallas.edu/bbcswebdav/pid-5336513-dt-content-rid-124019835_1/xid-124019835_1
Alpha is 10
[game-tree] 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? https://elearning.utdallas.edu/bbcswebdav/pid-5336513-dt-content-rid-124019939_1/xid-124019939_1
Alpha is negative infinity
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.In this strategy, the root node is expanded first, then all the nodes generated by the root node are expanded next, and then their successors, and so on.
Breadth-first search
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
______ 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
Depth-First search is Complete.
False
Depth-First search is Optimal.
False
Depth-Limited search is Complete.
False
_____ algorithm is a stochastic hill-climbing search in which a large population of states is maintained. New states are generated by mutation and by crossover, which combines pairs of states from the population.
Genetic
This _____ search strategy tries to expand the node that is closest to the goal, on the grounds that this is likely to lead to a solution quickly. Thus, it evaluates nodes by using just the heuristic function; that is, f (n) = h(n).
Greedy best-first search
_______ 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
Breadth-First search is Complete.
True
Iterative-Deepening search is Complete.
True
A well-known way to define machine intelligence is _____
Turing Test
_____ finds the cheapest solution provided a simple requirement is met: the cost of a path must never decrease as we go along the path.
Uniform cost 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 heuristic h*(n) is ______ if for every node n, h*(n) ≤ h(n), where h(n) is the true cost to reach the goal state from n.
admissible
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
Minimax is a ________.
algorithm
An agent is _____
autonomous and situated in an environment
Hill climbing is a(n) ______.
best-first search
_____ is to simultaneously search both forward from the initial state and backward from the goal, and stop when the two searches meet in the middle.
bidirectional search
The Space complexity of Depth-Limited search is _____.
bl (b times l)
AI problems tend to involve ______.
combinatorial explosion of running time
If a heuristic h is ______, then A* using GRAPH-SEARCH is optimal.
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
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) https://elearning.utdallas.edu/bbcswebdav/pid-5336513-dt-content-rid-124019752_1/xid-124019752_1
less than or equal to 1
The assumption that a game opponent will make the best possible move is made in _____.
minimax algorithm
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
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
A drawback of hill climbing is _____
tendency to become stuck at local maxima
The breadth-first search ______.
uses a queue
The depth-first search _____.
uses a stack
