Explanation: Sometimes minimum heuristics can be used, sometimes maximum heuristics function can be used. It depends upon the application on which the algorithm is applied. 10. In greedy approach evaluation function is
A. Heuristic function
B. Path cost from start node to current node
C. Path cost from start node to current node + Heuristic cost
D. Average of Path cost from start node to current node and Heuristic cost
Answer:A
Explanation: Sometimes minimum heuristics can be used, sometimes maximum heuristics function can be used. It depends upon the application on which the algorithm is applied. 10. In greedy approach evaluation function is
A. Heuristic function B. Path cost from start node to current node C. Path cost from start node to current node + Heuristic cost D. Average of Path cost from start node to current node and Heuristic cost
Explanation: Greedy best-first search3 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: f (n) = h(n). Sanfoundry Global Education & Learning Series – Artificial Intelligence.