Heuristics for Problem Solving (OCR A-Level Computer Science): Flashcards

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Heuristics for Problem Solving
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What is a heuristic?

Practical method to find solutions quickly, not always optimal

What is the purpose of heuristics?

Find 'good enough' solutions rather than optimal ones

When are heuristics most useful?

Complex problems where perfect solution takes too long

Example applications of heuristics

Pathfinding, optimisation problems, game strategies

What A* Algorithm combines

Dijkstra's algorithm with a heuristic for efficiency

g(n)g(n) in A* Algorithm

Actual cost to reach node nn from start

h(n)h(n) in A* Algorithm

Heuristic estimate of cost to reach goal from node nn

A* total cost function formula

f(n)=g(n)+h(n)f(n) = g(n) + h(n)

Manhattan Distance formula

h(n)=x1x2+y1y2h(n) = |x_1 - x_2| + |y_1 - y_2|

Manhattan Distance purpose

Estimates distance to goal in grid-based pathfinding

Main efficiency benefit of heuristics

Reduces time and computational resources required

Main drawback of heuristics

May not always produce the optimal solution

Chess AI heuristic factors

Material balance, piece mobility, control of centre

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