Suppose two teams, A and B, are playing a match to see who is the first to win games (for some particular n). We can suppose that A and B are equally competent, so each has a 50% chance of winning any particular game. Suppose they have already played i+j games, of which A has won i and B has won j. Give an efficient algorithm to compute the probability that A will go on to win the match. For example, if i=n-1 and j=n-3 then the probability that A will win the match is 78, since it must win any of the next three games.

Short Answer

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To solve the given problem, use dynamic programming approach.78,i=n-1andj=n-3,i+j

Step by step solution

01

Dynamic programming approach.

In dynamic programming there are all possibilities and more time as compared to greedy programming. and the Dynamic programming approach always gives the accurate or correct answer. In dynamic programming have to compute only distinct function call because as soon as compute and store in one data structure so that after this reuse afterward if it is needed.

02

Defining Recursive Relation and Implementation of Algorithm.

Let us suppose P (i,j ) is the probability for A to win the first n games.

Given that, i = Number of match A has won

And j=Number of match B has won

So, there are two conditions they are,

If P (i,j )=1 where i > 0 and j=1 this mean the probability of A to win is ‘one’.

If P (i,j )=0 where i > 0 and j=1 , this means the probability of A for won is ‘zero’.

Now for rest of the value of 'i' and 'j' then the value of evaluations is,

pi,j=12Pi,j+1+Pi+1

After that let P (0,j ) is as zero or one then compare each situation.

P0,i=1andPi,1=0ifn-j>0andn-i=0Pn-i,j-i=1ifn-j=0andn-i>1

Here, A will go on to win the match. For example, if i=n-1 and j=n-3 then the probability that A will win the match is 78, since it must win any of the next three games.

ifn-i>1andn-j>1Pn-i,j-i=12Pi-1,j+Pi,j-2returnPn-i,j-i

By approach of dynamic programming for playing a match to see who is the first to win number of games where equally competent and each has fifty percent chance of winning any particular game and the probability that A will go for to win the match an A will go on to win the match. ifi=n-1 and j=n-3 then the probability that A will win and it will take time of O(n) Since, we are playing ‘n’ times, so our algorithm will trace output of n output. Thus, runtime would be O(n)

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Most popular questions from this chapter

A certain string-processing language offers a primitive operation which splits a string into two pieces. Since this operation involves copying the original string, it takes n units of time for a string of length n, regardless of the location of the cut. Suppose, now, that you want to break a string into many pieces. The order in which the breaks are made can affect the total running time. For example, if you want to cut a 20-character string at positions 3 and 10, then making the first cut at position 3 incurs a total cost of 20+17=37, while doing position first has a better cost of 20+17=37.

Give a dynamic programming algorithm that, given the locations of m cuts in a string of length , finds the minimum cost of breaking the string into m +1 pieces.

Yuckdonald’s is considering opening a series of restaurant along Quaint Valley Highway(QVH). The n possible locations are along a straight line, and the distances of these locations from the start of QVH are, in miles and in increasing order,m1,m22,....,mn.. The constraints are as follows:

At each location, Yuckdonald may open at most one restaurant. The expected profit from opening a restaurant at location i is given aspi, wherepi>0andi=1,2,,n.

Any two restaurants should be at least k miles apart, where k is a positive integer.

Give an efficient algorithm to compute the maximum expected total profit subject to the given constraints.

Consider the following 3-PARTITION problem. Given integersa1,...,an, we want to determine whether it is possible to partition of {1,...,n} into three disjoint subsets I,J,Ksuch that

aiiI=ajjJ=akkk=13aii1 .

For example, for input(1,2,3,4,4,5,8) the answer is yes, because there is the partition(1,8),(4,5),(2,3,4). On the other hand, for input(2,2,3,5) the answer is no. Devise and analyze a dynamic programming algorithm3-PARTITION for that runs in time polynomial in n and in Σiai.

Time and space complexity of dynamic programming. Our dynamic programming algorithm for computing the edit distance between strings of length m and n creates a table of size n×mand therefore needs O (mn) time and space. In practice, it will run out of space long before it runs out of time. How can this space requirement be reduced?

  1. Show that if we just want to compute the value of the edit distance (rather than the optimal sequence of edits), then only O(n) space is needed, because only a small portion of the table needs to be maintained at any given time.
  2. Now suppose that we also want the optimal sequence of edits. As we saw earlier, this problem can be recast in terms of a corresponding grid-shaped dag, in which the goal is to find the optimal path from node (0,0) to node (n,m). It will be convenient to work with this formulation, and while we’re talking about convenience, we might as well also assume that is a power of 2.
    Let’s start with a small addition to the edit distance algorithm that will turn out to be very useful. The optimal path in the dag must pass through an intermediate node (k,m2) for some k; show how the algorithm can be modified to also return this value k.
  3. Now consider a recursive scheme:
    Procedure find-path((0,0)(n,m))
    Compute the value kabove
    find-path ((0,0)k,m2)
    find-path k,m2n,m
    concatenate these two paths, with kin the middle.
    Show that this scheme can be made to run inO (mn) time and O(n) space.

The garage sale problem (courtesy of Professor Lofti Zadeh). On a given Sunday morning, there are n garage sales going on, g1,g2,g3............gn. For each garage sale gj, you have an estimate of its value to you, vj. For any two garage sales you have an estimate of the transportation cost dijof getting from gito gj. You are also given the costs d0jand dj0of going between your home and each garage sale. You want to find a tour of a subset of the given garage sales, starting and ending at home, that maximizes your total benefit minus your total transportation costs. Give an algorithm that solves this problem in time O(n22n).

(Hint: This is closely related to the traveling salesman problem.)

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