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 ____________ is/are useful when the original formulation of a problem is altered in some way, typically because the set of constraints to consider evolves because of the environment. a) Static CSPs b) Dynamic CSPs c) Flexible CSPs d) None of the above    0  6
Solving a constraint satisfaction problem on a finite domain is an/a ___________ problem with respect to the domain size. a) P complete b) NP complete c) NP hard d) Domain dependent    0  7
Constraint satisfaction problems on finite domains are typically solved using a form of ___________. a) Search Algorithms b) Heuristic Search Algorithms c) Greedy Search Algorithms d) DFS/BFS Search Algorithms    0  6
Consider a problem of preparing a schedule for a class of student. This problem is a type of a) Search Problem b) Backtrack Problem c) CSP d) Planning Problem    0  6
The BACKTRACKING-SEARCH algorithm in Figure 5.3 has a very simple policy for what to do when a branch of the search fails: back up to the preceding variable and try a different value for it. This is called chronological-backtracking. It is also possible to go all the way to set of variable that caused failure. State whether True or False. a) True b) False    0  6
To overcome the need to backtrack in constraint satisfaction problem can be eliminated by a) Forward Searching b) Constraint Propagation c) Backtrack after a forward search d) Omitting the constraints and focusing only on goals    0  7
To overcome the need to backtrack in constraint satisfaction problem can be eliminated by a) Forward Searching b) Constraint Propagation c) Backtrack after a forward search d) Omitting the constraints and focusing only on goals    0  7
The term ___________ is used for a depth-first search that chooses values for one variable at a time and returns when a variable has no legal values left to assign. a) Forward search b) Backtrack search c) Hill algorithm d) Reverse-Down-Hill search    0  7
 What among the following constitutes to the incremental formulation of CSP? a) Path cost b) Goal cost c) Successor function d) Objective function e) Initial state    0  6
Which of the Following problems can be modeled as CSP? a) 8-Puzzle problem b) 8-Queen problem c) Map coloring problem d) Sudoku    0  6
_________________ are mathematical problems defined as a set of objects whose state must satisfy a number of constraints or limitations. a) Constraints Satisfaction Problems b) Uninformed Search Problems c) Local Search Problems d) Only a) and b)    0  8
___________ algorithm keeps track of k states rather than just one. a) Hill-Climbing search b) Local Beam search c) Stochastic hill-climbing search d) Random restart hill-climbing search    0  9
Hill-Climbing approach stuck for the following reasons a) Local maxima b) Ridges c) Plateaux d) All of above    0  6
Hill climbing sometimes called ____________ because it grabs a good neighbor state without thinking ahead about where to go next. a) Needy local search b) Heuristic local search c) Greedy local search d) Optimal local search    0  6
Stochastic hill climbing chooses at random from among the uphill moves; the probability of selection can vary with the steepness of the uphil1 move. a) True b) False    0  6
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To overcome the need to backtrack in constraint satisfaction problem can be eliminated by a) Forward Searching b) Constraint Propagation c) Backtrack after a forward search d) Omitting the constraints and focusing only on goals 7
. What is state space? a) The whole problem b) Your Definition to a problem c) Problem you design d) Representing your problem with variable and parameter 4
An agent is composed of, a) Architecture b) Agent Function c) Perception Sequence d) Architecture and Program 4
Hill-Climbing algorithm terminates when, a) Stopping criterion met b) Global Min/Max is achieved c) No neighbor has higher value d) Local Min/Max is achieved 4
Artificial Intelligence has its expansion in the following application. (Mark all that apply) a) Planning and Scheduling b) Game Playing c) Diagnosis d) Robotics e) All of the above 8
 A problem solving approach works well for a) 8-Puzzle problem b) 8-queen problem c) Finding a optimal path from a given source to a destination d) Mars Hover (Robot Navigation) 4
 What is the expansion if PEAS in task environment? a) Peer, Environment, Actuators, Sense b) Perceiving, Enivornment, Actuators, Sensors c) Performance, Environment, Actuators, Sensors, d) None of the mentioned 4
Which environment is called as semidynamic? a) Environment does not change with the passage of time b) Agent performance changes c) Environment will be changed d) Both a & b 4
Performance Measures are fixed for all agents. State true or false a) True b) False 4
Which method is used to search better by learning? a) Best-first search b) Depth-first search c) Metalevel state space d) None of the mentioned 4
What is not represented by using propositional logic? a) Objects b) Relations c) Both a & b d) None of the mentioned 5
___________ algorithm keeps track of k states rather than just one. a) Hill-Climbing search b) Local Beam search c) Stochastic hill-climbing search d) Random restart hill-climbing search 9
Though local search algorithms are not systematic, key advantages would include a) Less memory b) More time c) Finds a solution in large infinite space d) No optimum solution 4
Which agent enables the deliberation about the computational entities and actions? a) Hybrid b) Reflective c) Relational d) None of the mentioned 4
The BACKTRACKING-SEARCH algorithm in Figure 5.3 has a very simple policy for what to do when a branch of the search fails: back up to the preceding variable and try a different value for it. This is called chronological-backtracking. It is also possible to go all the way to set of variable that caused failure. State whether True or False. a) True b) False 6
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