UGC NET CSE | Junet 2015 | Part 3 | Question: 59

Question

Match the following with respect to heuristic search techniques $:$

$\begin{array}{clcl} & \textbf{List – I} && \textbf{List – II} \\ \text{(a)} & \text{Steepest-acccent Hill} & \text{(i)} & \text{Keeps track of all partial paths which can} \\ & \text{Climbing}&&\text{be candiadate for further explaination} \\ \text{(b)} & \text{Branch-and-bound} & \text{(ii)} & \text{Discover problem state(s) that satisfy } \\ & \text{}&&\text{a set of constraints} \\ \text{(c)} & \text{Constraint satisfaction} & \text{(iii)} & \text{Detects difference between current state} \\ & \text{}&&\text{and goal state} \\ \text{(d)} & \text{Means-end-analysis} & \text{(iv)} & \text{Considers all moves from current state} \\ & \text{}&&\text{and selects best move} \\  \end{array}$

$\textbf{Codes :}$

• A. $\text{(a)-(i), (b)-(iv), (c)-(iii), (d)-(ii)}$
• B. $\text{(a)-(iv), (b)-(i), (c)-(ii), (d)-(iii)}$
• C. $\text{(a)-(iii), (b)-(iv), (c)-(i), (d)-(ii)}$
• D. $\text{(a)-(iv), (b)-(ii), (c)-(i), (d)-(iii)}$

Answer 1

Ans will be B

Steepest accent Hill Climbing  (Looks for best move which may or may not be optimal)

Branch - and - bound Keeps track of all partial paths which can be candidate for further exploration 

The idea of a branch-and-bound search is to maintain the lowest-cost path to a goal found so far, and its cost. Suppose this cost is bound. If the search encounters a path p such that cost(p)+h(p) ≥ bound, path pcan be pruned. If a non-pruned path to a goal is found, it must be better than the previous best path. This new solution is remembered and bound is set to the cost of this new solution. It then keeps searching for a better solution.

Constraint satisfaction (Discover problem state(s) that satisfy a set of constraints)

Means - end - analysis Detects difference between current state and goal state

Comments

Here options are wrong....

A-iv       B-i      c-ii      d-III

Hill Climbing    -select best moves

Branch and bound- keeps track of all partial path

Constraints satisfaction - discover problem states

Means -end-analysis - detect difference between current and goal state