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External A*

External A*. Stefan Edelkamp, Shahid Jabbar (ich) University of Dortmund, Germany and Stefan Schrödl (DaimlerChrysler, CA). A* Algorithm. A.k.a Goal-directed dijkstra A heuristic estimate is used to guide the search.

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External A*

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  1. External A* Stefan Edelkamp, Shahid Jabbar (ich) University of Dortmund, Germany and Stefan Schrödl (DaimlerChrysler, CA)

  2. A* Algorithm • A.k.a Goal-directed dijkstra • A heuristic estimate is used to guide the search. • E.g. Straight line distance from the current node to the goal in case of a graph with a geometric layout. • Reweighting: • w’(u,v) = w(u,v) – h(u) + h(v) External A*

  3. Problems (It’s a big big world for a small small memory) • A* needs to store all the states during exploration. • A* generates large amount of duplicates that can be removed using an internal hash table – only if it can fit in the main memory. • A* do not exhibit any locality of expansion. For large state spaces, standard virtual memory management can result in excessive page faults. External A*

  4. A bit of History • Munagala and Ranade: • Generated states flushed to the disk for every BFS level. • No hash table. • Duplicates are removed by sorting the nodes according to the indices and doing an scan and compaction phase. • Before expanding a layer t, the nodes in the layer t-1 and t-2 are subtracted from t. • O(|V| + sort(|V| + |E|)) I/Os. External A*

  5. A bit of History (contd…) • Further improved by Mehlhorn & Meyer to • O(√(|V| ∙ scan(|V| + |E|)) + sort(|V| + |E|)) I/Os. • Korf presented External BFS for implicit graphs with the name Delayed duplicate detection for frontier search. • Keep a level in the main memory until it exceeds a certain bound. • If it does, sort it and flush to the disk. • When a level is finished, merge the presorted buffers to get a sorted file and remove the duplicates External A*

  6. Restriction on the domain • Implicit state space – generated on the fly –> no adjacency list • Unweighted • Undirected • Consistent Heuristic External A*

  7. Take a closer look Ah ha! It’s a Bucket of states h • Implicit, unweighted, undirected graphs • Consistent heurisitc estimates. => ∆h ={-1,0,1} g External A*

  8. Insert state Flush when full Buffer in internal memory File on disk Bucket • A Bucket is a set of states, residing on the disk, having the same (g, h) value, • Where, g = number of transitions needed to transform the initial state to the states of the bucket, • and h = Estimated distance of the bucket’s state to the goal • No state is inserted again in a bucket that is expanded • If Active (being read or written), represented internally by a small buffer. External A*

  9. External A* • Buckets represent temporal locality – cache efficient order of expansion. • If we store the states in the same bucket together we can exploit the spatial locality. • Munagala and Ranade’s BFS and Korf’s delayed duplicate detection for implicit graphs. External A* External A*

  10. External A* - pseudocode Procedure External A* Bucket(0, h(I))  {I} fminh(I) while (fmin ≠ ∞) g min{i | Bucket(i, fmin − i) ≠ } while (gmin ≤ fmin) hfmin − g Bucket(g, h)  remove duplicates from Bucket(g, h) Bucket(g, h) Bucket(g, h) \ (Bucket(g − 1, h) U Bucket(g − 2, h)) // Subtraction A(fmin),A(fmin + 1),A(fmin + 2)  N(Bucket(g, h)) // Generate Neighbours Bucket(g + 1, h + 1)  A(fmin + 2) Bucket(g + 1, h)  A(fmin + 1) U Bucket(g + 1, h) Bucket(g + 1, h − 1)  A(fmin) U Bucket(g + 1, h − 1) gg + 1 fmin min{i + j > fmin | Bucket(i, j) ≠ } U {∞} External A*

  11. Complexity Analysis • Internal A* => Each edge is looked at most once. • Duplicates Removal: • Sorting the green bucket having one state for every edge from the 3 black buckets. • Scanning and compaction. • O(sort(|E|)) • Subtraction: • Removing states of orange buckets (duplicates free) from the green one. • O(scan(|V|) + scan(|E|)) External A*

  12. I/O Performance of External A* Theorem: The complexity of External A* in an implicit unweighted and undirected graph with a consistent estimate is bounded by O(sort(|E|) + scan(|V|)) I/Os. External A*

  13. 15-Puzzle External A*

  14. Experimental Results – Test Instances External A*

  15. Test Run – Generated states External A*

  16. Test Run - Duplicates External A*

  17. Exp. Results – Generated nodes External A*

  18. Cache-Efficient Behaviour: File on disk Internal Buffers CPU External A*

  19. Conclusion • A* for secondary storage with an I/O complexity of O(sort(|E|) + scan(|V|)) . • Given that Delayed Duplication Detection has to be performed, the bound is I/O optimal. • File-based priority queue. • Hash table replaced by Delayed Duplicate Detection. • Successfully implemented to solve Korf’s Largest instance in secondary memory. • In case of non-uniformly weighted graphs with small integer weights in {1, …, C}. • O(sort(|E|) + C ∙ scan(|V|)) External A*

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