Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Macro-operators: a weak method for learning
Artificial Intelligence - Lecture notes in computer science 178
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
SOAR: an architecture for general intelligence
Artificial Intelligence
Principles of artificial intelligence
Principles of artificial intelligence
The History Heuristic and Alpha-Beta Search Enhancements in Practice
IEEE Transactions on Pattern Analysis and Machine Intelligence
Single-Agent Parallel Window Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient memory-bounded search methods
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Performance measurement and analysis of certain search algorithms.
Performance measurement and analysis of certain search algorithms.
Unifying Single-Agent and Two-Player Search
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Toward perpetually organized unit-load warehouses
Computers and Industrial Engineering
Solving the 8-puzzle problem using genetic programming
Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
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The 8-puzzle is the largest puzzle of its type that can be completely solved. It is simple, and yet obeys a combinatorially large problem space of 91/2 states. The N × N extension of the 8-puzzle is NP-hard. In the first part of this paper, we present complete statistical data based on an exhaustive evaluation of all possible tile configurations. Our results include data on the expected solution lengths, the 'easiest' and 'worst' configurations, and the density and distribution of solution nodes in the search tree. In our second set of experiments, we used the 8-puzzle as a workbench model to evaluate the benefit of node ordering schemes in Iterative-Deepening A* (IDA*). One highlight of our results is that almost all IDA* implementations perform worse than would be possible with a simple random ordering of the operators.