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

One of the main cons of hill-climbing search is, a) Terminates at local optimum b) Terminates at global optimum c) Does not find optimum solution d) Fail to find a solution

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

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

Hill-Climbing approach stuck for the following reasons a) Local maxima b) Ridges c) Plateaux d) All of above

___________ 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

_________________ 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)

Which of the Following problems can be modeled as CSP? a) 8-Puzzle problem b) 8-Queen problem c) Map coloring problem d) Sudoku

 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

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

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

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

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

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

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