SMA*

SMA* or Simplified Memory Bounded A* is a shortest path algorithm based on the A* algorithm. The main advantage of SMA* is that it uses a bounded memory, while the A* algorithm might need exponential memory. All other characteristics of SMA* are inherited from A*.

SMA* or Simplified Memory Bounded A* is a shortest path algorithm based on the A* algorithm. The main advantage of SMA* is that it uses a bounded memory, while the A* algorithm might need exponential memory. All other characteristics of SMA* are inherited from A*. function simple memory bounded A*-star(problem): path queue: set of nodes, ordered by f-cost; begin queue.insert(problem.root-node); while True do begin if queue.empty() then return failure; //there is no solution that fits in the given memory node := queue.begin(); // min-f-cost-node if problem.is-goal(node) then return success; s := next-successor(node) if !problem.is-goal(s) && depth(s) == max_depth then f(s) := inf; // there is no memory left to go past s, so the entire path is useless else f(s) := max(f(node), g(s) + h(s)); // f-value of the successor is the maximum of // f-value of the parent and // heuristic of the successor + path length to the successor end if if no more successors then update f-cost of node and those of its ancestors if needed if node.successors ⊆ queue then queue.remove(node); // all children have already been added to the queue via a shorter way if memory is full then begin bad Node := shallowest node with highest f-cost; for parent in bad Node.parents do begin parent.successors.remove(bad Node); if needed then queue.insert(parent); end for end if queue.insert(s); end while end Simplified Memory Bounded A Star Search Algorithm | SMA* Search | Solved Example in by Mahesh Huddar ==References==

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