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The maximizer has to keep in view that what choices will be available to the minimizer on the next step. The maximizer wishes to maximize the score so apparently 7 being the maximum score, the maximizer should go to C and then to G.

Its early in the morning and assume that no other person is awake in the town who can guide him on the way. The numbers on the nodes are the estimated distance on the node from the goal state. Hence a huge amount of computation power and time is required in solving the optimal search problems in a brute force manner. Now after observing the handluts side of the tree, this score will either increase or will remain the same as this level is for the css607.

Clearly identify the four components of problem solving in the above statement, i. Is best first search always the best strategy? To develop this stance he uses a look ahead thinking strategy. We see that C is a leaf node so we bind C too as shown in the next diagram.

Their goals are usually contrary to each other. But one thing that lacks in both is that whenever they find a solution they immediately stop.

## Artificial Intelligence (CS607)

The values on the edges are the distance between two adjacent cities. Now A and E are equally good nodes so we arbitrarily choose amongst them, and we move to A. Hence we block all the further sub-trees along this path, as shown in the diagram below. Will it always guarantee the best solution? 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.

Notice further that if player one puts a cross in any box, player-two will intelligently try to make a move that would leave player-one with minimum chance to win, that is, he will try to stop player- one from completing a line of crosses and at the same time will try to complete his line of zeros. We start with a tree with goodness of every node mentioned on it. Use your suggested solutions to the above mention problems if any of them are encountered.

Show the state of the data structure Q and the visited list clearly at every step. S is the initial state and D is the goal state.

We will demonstrate this improvement with an example. Q3 Given the following tree. Suggest Improvements in the Algorithm. Positive numbers, by convention indicate favor to one player.

We proceed in a Best First Search manner. So we ignore cs067 further paths ahead of the path S D A B. We construct the tree corresponding to the graph above. The basic idea was to reduce the search space by binding the paths that exceed the path length from S to G.

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

So traveling further from S D Handots B to some other node will make the path longer. At last from H we find L as the best. The static evaluation scores for each leaf node are written under it. Dynamic Programming The idea of estimates is that we can travel in the solution space using a heuristic estimate.

So we explore D. A problem here is that if we go with an overestimate of the remaining distance then we might hqndouts a solution that is somewhere nearby.

The other player is called minimizing player or minimizer.