The average complexity of depth-first search with backtracking and cutoff
IBM Journal of Research and Development
Efficient search techniques—an empirical study of the N-Queens problem
IBM Journal of Research and Development
A problem simplification approach that generates heuristics for constraint-satisfaction problems
Machine intelligence 11
Divide and conquer under global constraints: a solution to the N-queens problem
Journal of Parallel and Distributed Computing
An almost perfect heuristic for the N nonattacking queens problem
Information Processing Letters
Explicit solutions to the N-queens problem for all N
ACM SIGART Bulletin
3,000,000 Queens in less than one minute
ACM SIGART Bulletin
Solving the n-queens problem using genetic algorithms
SAC '92 Proceedings of the 1992 ACM/SIGAPP symposium on Applied computing: technological challenges of the 1990's
Different perspectives of the N-Queens problem
CSC '92 Proceedings of the 1992 ACM annual conference on Communications
Backtrack programming techniques
Communications of the ACM
Efficient Local Search with Conflict Minimization: A Case Study of the n-Queens Problem
IEEE Transactions on Knowledge and Data Engineering
Efficient Sorting and Routing on Reconfigurable Meshes Using Restricted Bus Length
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
A graph model for deadlock prevention.
A graph model for deadlock prevention.
An efficient non-probabilistic search algorithm for the N-queens problem
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
Exploiting CPU Bit Parallel Operations to Improve Efficiency in Search
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
MINION: A Fast, Scalable, Constraint Solver
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Search rearrangement backtracking and polynomial average time
Artificial Intelligence
Using Graphs to Derive CSP Heuristics and its Application to Sudoku
ICTAI '09 Proceedings of the 2009 21st IEEE International Conference on Tools with Artificial Intelligence
Solving large-scale constraint satisfaction and scheduling problems using a heuristic repair method
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
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This paper presents a set of new decision rules for exact search in N-Queens. Apart from new tiebreaking strategies for value and variable ordering, we introduce the notion of `free diagonal' for decision taking at each step of the search. With the proposed new decision heuristic the number of subproblems needed to enumerate the first K solutions (typically K = 1, 10 and 100) is greatly reduced w.r.t. other algorithms and constitutes empirical evidence that the average solution density (or its inverse, the number of subproblems per solution) remains constant independent of N. Specifically finding a valid configuration was backtrack free in 994 cases out of 1,000, an almost perfect decision ratio. This research is part of a bigger project which aims at deriving new decision rules for CSP domains by evaluating, at each step, a constraint value graph G c . N-Queens has adapted well to this strategy: domain independent rules are inferred directly from G c whereas domain dependent knowledge is represented by an induced hypergraph over G c and computed by similar domain independent techniques. Prior work on the Number Place problem also yielded similar encouraging results.