Additive Pattern Database Heuristics

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2.4.1 Limitations of statically-partitioned database heuristics●●They fail to capture interactions among tiles indifferent groups of the partition.A different approach to additive patterndatabases: dynamically-partitioned databaseheuristics
3. Dynamically-Partitioned <strong>Database</strong><strong>Heuristics</strong>3.1 Computing the Pairwise Distances, or Gasserrefers it as 2-tile pattern database :– a table which contains for each pair of tiles, andeach possible pair of positions they could occupy,the number of moves required of those two tiles tomove them to their goal positions– How to compute such tables: for each pair oftiles, we perform a single breadth-first search,starting from the goal state.
Page 1 and 2: Additive Pattern Database Heuristic
Page 3 and 4: ●●The most effective way to imp
Page 5 and 6: ●●●An optimal solution to the
Page 7 and 8: 1.3 two main contributions of thisp
Page 9 and 10: 2. Previous Work on AdmissibleHeuri
Page 11: Statically-Partitioned Additivedata
Page 15 and 16: ●For each state of the search , t
Page 17 and 18: Dynamically-Partitioned databaseHeu
Page 19 and 20: 4.2.2 fifteen puzzle partition
Page 21 and 22: 4.2.3 Twenty-four puzzle
Page 23 and 24: 4.2.4 Thirty-five puzzle
Page 25 and 26: 4.2.5 Discussion of the tile puzzle
Page 27 and 28: Experimental results for the 15-dis
Page 29 and 30: 6. Vertex Cover
Page 32 and 33: 7. General Characterization of theM
Page 34 and 35: 7.2.2 Partial pattern databases●
Page 36 and 37: The steps for the staticallypartiti
Page 38 and 39: 7.4 Differences between theapplicat
Page 40 and 41: 8.2 Conclusions and Further Work●

Additive Pattern Database Heuristics

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