Divide and conquer: How Microsoft researchers used AI to master Ms. Pac-Man
Microsoft
Divide and conquer: How Microsoft researchers used AI to master Ms. Pac-Man
Microsoft researchers have created an artificial intelligence-based system that learned how to get the maximum score on the addictive 1980s video game Ms. Pac-Man, using a divide-and-conquer method that could have broad implications for teaching AI agents to do complex tasks that augment human capabilities. Read more at Next at Microsoft: aka ...
Jun 14, 2017
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Consider a divide and conquer algorithm which takes an input set P with |P| = n and divides it into two pieces, P1 and P2. The two pieces are such that P1 ∩ P2 = φ, P1 ∪ P2 = P, and |P1| ≥ (n/3) and |P2| ≥ (n/3). The algorithm recursively solves the problem on P1 and P2 and merges the solution in O(n^1.5) time. In the base case, when the problem is of size 1, the algorithm returns the correct solution in 1 step. Show that the running time of this algorithm is O(n^1.5). You will still re
Consider a divide and conquer algorithm which takes an input set P with |P| = n and divides it into two pieces, P1 and P2. The two pieces are such that P1 ∩ P2 = φ, P1 ∪ P2 = P, and |P1| ≥ (n/3) and |P2| ≥ (n/3). The algorithm recursively solves the problem on P1 and P2 and merges the solution in O(n^1.5) time. In the base case, when the problem is of size 1, the algorithm returns the correct solution in 1 step. Show that the running time of this algorithm is O(n^1.5). You will still re
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Consider a divide and conquer algorithm which takes an input set P with |P| = n and divides it into two pieces, P1 and P2. The two pieces are such that P1 ∩ P2 = φ, P1 ∪ P2 = P, and |P1| ≥ (n/3) and |P2| ≥ (n/3). The algorithm recursively solves the problem on P1 and P2 and merges the solution in O(n^1.5) time. In the base case, when the problem is of size 1, the algorithm returns the correct solution in 1 step. Show that the running time of this algorithm is O(n^1.5). You will still re
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