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Alpha Beta Pruning Algorithm Assignment Help


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What is Alpha Beta Pruning algorithm?


1) By the alpha beta pruning we are able to enhance the performance of the minimax algorithm.

2) Obtains its name two bounds which are transferred combined over the calculation, that limit the set of feasible solutions based on the section of the search tree which had been already observed particularly.

3) Upper bound : have the possible solutions when Beta is the minimum upper 

4) Lower bound : have the possible solution when alpha is the lower bound


Therefore, when any kind of new node considered as a possible path to the solution, it could work if:


( α <= N <= β)  // here N is called current estimate of the value of the node.


Function MAX VALUE (state, game, α(alpha), β(beta)) returns the   minimax value ofstate
Inputs: state, initial state in game
Game, game_description
α(alpha)//  the most effective report for  max across the path tostate
β, the most effective   report min across the pathtostate

if test of   the cutoff is test(statethen return eval(state)
for every p” in successors(state) do
α (alpha)<-max(α,min value(p, game α(alpha), β(beta)) 
if α >=   β //when   alpha is greater than equal to beta then return beta
then return β  
end
return α 


function min-value(state, game, α, β)return the minimax value ofstate
if cutoff test (statethen return eval(state)
for every p” in successors(state) do
β <-min (β,max value (p, game, α, β))
if β <=   α then return   α // beta is   less than equal to alpha
end
return β



ALPHA BETA Properties


1) It is not affected the final result of the purning.

2) Perfect ordering improves effectiveness of pruning

3) With good move ordering, than time complexity is =O(b power( m/2 ))

4) A straightforward example of the value involving reasoning regarding that computations tend to be applicable.



ALPHA BETA Effectiveness


1) Guaranteed to compute same root value as minimax

2) Alpha Beta Pruning Algorithm of the worst case is no pruning, same as minimax(O( b power d ))

3) Alpha Beta Pruning Algorithm of the Best case is whenever each player's greatest proceed may be the very first option analyzed, you analyzed just O(b power( d/2 )) nodes. Helping you to look for twice as serious




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