Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Randomized algorithms
Suffix Tree Automata in State Space Search
KI '97 Proceedings of the 21st Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Complexity analysis admissible heuristic search
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Recent Progress in the Design and Analysis of Admissible Heuristic Functions
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
Prediction of Regular Search Tree Growth by Spectral Analysis
KI '01 Proceedings of the Joint German/Austrian Conference on AI: Advances in Artificial Intelligence
Finding Optimal Solutions to Atomix
KI '01 Proceedings of the Joint German/Austrian Conference on AI: Advances in Artificial Intelligence
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Many problems, such as the sliding-tile puzzles, generate search trees where different nodes have different numbers of children, in this case depending on the position of the blank. We show how to calculate the asymptotic branching factors of such problems, and how to efficiently compute the exact numbers of nodes at a given depth. This information is important for determining the complexity of various search algorithms on these problems. In addition to the slidingg-tile puzzles, we also apply our technique to Rubik's Cube. While our techniques are fairly straightforward, the literature is full of incorrect branching factors for these problems, and the errors in several incorrect methods are fairly subtle.