CS607 HANDOUTS PDF

CS607 HANDOUTS PDF

Link to this post 22 Nov Download VU Artificial Intelligence – CS VU Lecture Handouts. Artificial Intelligence – CS Handouts Lecture 1 – · Artificial. Artificial Intelligence – CS VU Video Lectures. Watch Online Artificial Intelligence – CS VU Video Lectures. Artificial Intelligence – CS VU Lecture. Artificial Intelligence CS Download Complete Lectures Artificial VU Projects · Video Lectures · Handouts · Past Papers · Quizzes.

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We visit F and finally we reach G as shown in the subsequent diagrams. The other player is called minimizing player or minimizer. Given the following tree, use the hill climbing procedure to climb up the tree.

Dynamic Programming The idea of estimates is that we can travel in the solution space using a heuristic estimate. The minimizer has to keep in view that nandouts choices will be available to the maximizer on the next step.

To clarify the concept of adversarial search let us discuss a procedure called the minimax procedure. Next we visit E, then we visit B the child of E, we bound the sub-tree below B. The values on the links are the distances between the cities. The readers are required to go though the last portion of Lecture 10 for the explanation of this example, if required.

CS Artificial Intelligence Handouts List VU Courses for MCS – Master of Computer Science

We see that C is a leaf node so we bind C too as shown in the next diagram. Search the history of over billion web pages on the Internet.

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So we explore D. The simple idea of branch and bound is the following: S is the initial state and D is the goal state. For example the static evaluation scores for the left most leaf node is Suggest solutions to the commonly encountered problems that are local maxima, plateau problem and ridge problem.

We will focus on board games for simplicity The rode is a game tree represent board configuration and the branches indicate how moves can connect them.

Hence using dynamic programming we will ignore the whole sub-tree beneath D the child of A as shown in the next diagram. We will discuss the technique with the same example as that in branch-and- bound. Support your answer with small handoutts of a few trees.

They never consider that their might be more than one solution to the problem and the solution that they have ignored might be the optimal one.

So we ignore any further paths ahead of the path S D A B. There is no need to look at any other paths to or from Expanded f Never Expanded In the diagram you can see that cs670 can reach node D directly from S with a cost of 3 and via S A D with a cost of 6 hence we will never expand the path with the larger cost of reaching the same node. Now A and E are equally good nodes so vs607 arbitrarily choose amongst them, and we move to A.

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CS607 Handouts

The numbers on the nodes are the estimated distance on the node from the goal state. Hence both have different goals.

Suppose we start of with a game tree in the diagram below. Standing at S we handots that the best node is A with a value of 4 so we move to 4. He has to drive on his car but doesn’t know the way to air port. We have shown the sequence of steps in the diagrams below.

Artificial Intelligence (CS607)

Use your suggested solutions to the above mention problems if any of them are encountered. Q5 Discuss the problems in Hill Climbing. The number of branches in an exhaustive survey would be on the order of 10 hahdouts Hence best first search is a greedy approach will looks for the best amongst the available options and hence can sometimes reduce the searching time.

Support your answer with an example tree. Consider the following diagram. Many games can be modeled as trees as shown below.