lecture 14 heuristic search-a star algorithm
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Heuristic Search-A* AlgorithmLecture-14
Hema Kashyap
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A* Search• A* is a cornerstone name of many AI systems and has been used since it was
developed in 1968 by Peter Hart; Nils Nilsson and Bertram Raphael. It is thecombination of Dijkstra’s algorithm and Best first search. It can be used to solvemany kinds of problems. A* search finds the shortest path through a search spaceto goal state using heuristic function. This technique finds minimal cost solutionsand is directed to a goal state called A* search. In A*, the * is written for optimalitypurpose. The A* algorithm also finds the lowest cost path between the start andgoal state, where changing from one state to another requires some cost. A*requires heuristic function to evaluate the cost of path that passes through theparticular state. This algorithm is complete if the branching factor is finite andevery action has fixed cost. A* requires heuristic function to evaluate the cost ofpath that passes through the particular state. It can be defined by followingformula.
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A* Algorithm
1. Initialize: set OPEN=[s], CLOSED=[], g(s)=0, f(s)=h(s)
2. Fail: If OPEN=[], then terminate and fail
3. Select: Select a state with minimum cost ,n, from OPEN and save inCLOSED
4. Terminate: If n∈G then terminate with success and return f(s)
5. Expand: For each successors , m of n
For each successor, m, insert m in OPEN only if
if m∈ [OPEN∪CLOSED]
set g(m)= g[n]+C[n,m]
Set f(m)=g(m)+h(n)
if m∈[OPEN∪CLOSED]
set g(m)= min{g[m], g(n)+C[n,m]}
Set f(m)=g(m)+h(m)
If f[m] has decreased and m ∈ CLOSED move m to OPEN
6. Loop: Goto step 2
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A* Search-Properties
• Admissible: the algorithm A* is admissible . This means that
provided a solution exists, the first solution found by A* is an
optimal solution. A* is admissible under following conditions:
– In the state space graph
• Every node has a finite number of successors
• Every arc in the graph has a cost greater than some ε> 0
– Heuristic function: for every node n, h(n) ≤ h*(n)
• Complete: A* is also complete under the above conditions.
• Optimal: A* is optimally efficient for a given heuristic-of the
optimal search algorithm that expand search paths from the
root node, it can be shown that no other optimal algorithm will
expand fewer nodes and find a solution
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Advantages
• It is complete and optimal.
• It is the best one from other techniques.
• It is used to solve very complex problems.
• It is optimally efficient, i.e. there is no other optimal algorithm guaranteed to expand fewer nodes than A*.
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Disadvantages
• This algorithm is complete if the branching factor is finite and every action has fixed cost.
• The speed execution of A* search is highly dependant on the accuracy of the heuristic algorithm that is used to compute h (n).
• It has complexity problems.
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