UGC NET 2019 (A*)

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The video presents a multiple-choice question from the UGC NET Paper-2019 exam regarding search algorithms. The slide displays two lists for a matching exercise. List I includes (a) Greedy best first, (b) Lowest cost-first, and (c) A* algorithm. List II provides cost functions: (i) Minimal Cost (p)+h(p), (ii) Minimal h(p), and (iii) Minimal cost(p). The instructor systematically draws green lines to connect the algorithms in List I with their corresponding optimization criteria in List II. Specifically, 'Greedy best first' is linked to 'Minimal h(p)', 'Lowest cost-first' is linked to 'Minimal cost(p)', and 'A* algorithm' is linked to 'Minimal Cost (p)+h(p)'. After establishing these connections, the instructor identifies the correct option from the four choices provided at the bottom. The final selection is option 4, which corresponds to the sequence (a)-(ii), (b)-(iii), (c)-(i). This visual demonstration clarifies the distinct evaluation functions used by these three fundamental search strategies in artificial intelligence.

Chapters

  1. 0:00 – 0:21 00:00-00:21

    The instructor draws green lines connecting List I items to List II items. (a) connects to (ii), (b) connects to (iii), and (c) connects to (i). The instructor then underlines the text 'Minimal Cost (p)+h(p)' and points to option 4 as the correct answer.

The lecture segment focuses on matching search algorithms with their respective cost functions. Greedy best-first search minimizes the heuristic function h(p), representing the estimated cost to the goal. Lowest cost-first search minimizes the actual path cost g(p), often denoted as cost(p). The A* algorithm combines both by minimizing the sum f(p) = g(p) + h(p). The visual matching exercise reinforces these definitions for exam preparation.