Question: 1-) 2-) 3-) 4-) 5-) Given the following problem space where each edge is labeled with the cost to traverse that edge. Heuristic Function to

1-)

1-) 2-) 3-) 4-) 5-) Given the following problem space where each

2-)

edge is labeled with the cost to traverse that edge. Heuristic Function

3-)

to G: Q-mon> Owl 2 B D F a) Derive the search

4-)

tree according to the increasing node letter from left to right. b)

5-)

Find the shortest path from node Sto node G using the A*

Given the following problem space where each edge is labeled with the cost to traverse that edge. Heuristic Function to G: Q-mon> Owl 2 B D F a) Derive the search tree according to the increasing node letter from left to right. b) Find the shortest path from node Sto node G using the A* search algorithm. c) Find the shortest path from nodes to node G isang the Greedy search algorithm. P. q ve r aadaki nermeler olsun: P: ok alyorsun. Q: Kitaptaki her altrmay yaparsnz. R: Snfta A alrsnz Aadaki formulleri p, qver ve mantiksal balantlar kullanarak yazn: a) Kitaptaki her altrmay yaparsanz, bu dersten A alamazsnz. b) Bu dersten A almak iin ok almay ve kitaptaki her altrmay yapmay gerektirir. c) Ya kitaptaki her altrmay yaparsanz ya da ok alrsanz, o zaman bu dersten A alrsnz. d) ok almazsanz bu dersten A alamazsnz. c) Bu sinifta A alirsiniz ve kitaptaki her altrmay yaparsnz. Define the followings for an agent that can work as a cleaner in a factory (indoor): Goals: Percepts Sensors: Effectors: Actions Environment Performance measure For the agent given characterize the environment according to the following properties: Accessible: Deterministic: Episodic Discrete Consider the following samples observed: class 1: (0,1), (1.2), 2.11.2.2.3.1). (3.2).(4.2). (43) class 2:0.-11.0-2)(1-3).(2-2), 2-3), (3-2). (0,0), (05) #) Draw the 2 dimensional feature space. b) Classify the unknown vector X-(2,0) using k-nearest neighbor classifier with k - 5. Classify the unknown vector X-(2.0) using minimum distance classifier with Euclidean distance .) - sqrt((XI-YIP + (x2-y27 N Y Y d) Consider the following attributes observed for the Bayesian classifier is to be designed in order to classifiy the patterns as "flu" and "not flu". chis runny nose headache fever Y N Mild N Y Y Ne N Y N Strong N Mild N N N N Strong Y N Y Strong N N Mild Y Assuming that class I is "flu" and class 2 is not flu", compute the prior probabilities for the class 1 and class 2. Classify the following vector as class 1 flu" or class 2 mot flu". X-IN N Mild Y] N No

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