Artificial intelligence (Question - 6) ======================= One variation on the game of nim is described in Luger. The game begins with a single pile of stones. The move by a player consists of dividing a pile into two piles that contain an unequal number of stones. For example, if one pile contains six stones, it could be subdivided into piles of five and one, or four and two, but not three and three. The first player who cannot make a move loses the game. (6.1) Draw the complete game tree for this version of Nim if the start state consists of six stones. (6.2) Perform a minimax evaluation for this game. Let 1 denote a win and 0 a loss.

Artificial intelligence (Question - 6) ======================= One variation on the game of nim is described in Luger. The game begins with a single pile of stones. The move by a player consists of dividing a pile into two piles that contain an unequal number of stones. For example, if one pile contains six stones, it could be subdivided into piles of five and one, or four and two, but not three and three. The first player who cannot make a move loses the game. (6.1) Draw the complete game tree for this version of Nim if the start state consists of six stones. (6.2) Perform a minimax evaluation for this game. Let 1 denote a win and 0 a loss.

C++ for Engineers and Scientists

4th Edition

ISBN:9781133187844

Author:Bronson, Gary J.

Publisher:Bronson, Gary J.

Chapter4: Selection Structures

Section: Chapter Questions

Problem 14PP

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One variation on the game of nim is described in Luger. The game begins with a single pile of stones. The move by a player consists of dividing a pile into two piles that contain an unequal number of stones. For example, if one pile contains six stones, it could be subdivided into piles of five and one, or four and two, but not three and three. The first player who cannot make a move loses the game. (5.1) Draw the complete game tree for this version of Nim if the start state consists of six stones. (5.2) Perform a minimax evaluation for this game. Let 1 denote a win and 0 a loss.
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Artificial Intelligence - Local Search Starting from a randomly generated state of the 15-puzzle game (https://en.wikipedia.org/wiki/15_puzzle), steepest-ascent hill-climbing (the vanilla version of hill-climbing search) gets stuck 76% of the time, i.e., solving only 24% of problem instances. But it works very quickly, i.e., it takes just 6 steps on average when it succeeds and 5 steps when it gets stuck. In contrast, if sideways moves are allowed, this raises the percentage of problem instances solved by hill-climbing from 24% to 81%, with the success at a cost: the algorithm averages roughly 7 steps for each successful instance and 32 steps for each failure. Now suppose that we are implementing random-restart hill climbing (i.e., if a search fails, it keeps to try, and try, until it gets a success) by the following two versions: one uses vanilla steepest-ascent hill climbing, and the other one uses hill climbing with sideways moves. Can you please tell which version of…
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