Theoretical Computer Science
On-line scheduling of parallel jobs with runtime restrictions
Theoretical Computer Science
Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11-13, 1993
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
The Challenges of Real-Time AI
Computer
A fast algorithm for the maximum clique problem
Discrete Applied Mathematics - Sixth Twente Workshop on Graphs and Combinatorial Optimization
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Incomplete solution approach for the maximum clique finding in the real time systems
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Artificial intelligence in the maximum clique finding problem applications
ICAI'06 Proceedings of the 7th WSEAS International Conference on Automation & Information
An efficient branch-and-bound algorithm for finding a maximum clique
DMTCS'03 Proceedings of the 4th international conference on Discrete mathematics and theoretical computer science
Real-time systems: incomplete solution approach for the maximum-weighted clique problem
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
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In this paper a question of using artificial intelligence principles and an incomplete solution approach were explored for solving NP hard problems in the real-time systems using the maximum clique finding problem as an example. The incomplete solution is used to analyze different best known algorithms in the real-time environment, while artificial intelligence principles were implemented in a form of a meta-algorithm containing other problem specific algorithms. Experiments conducted in this paper have demonstrated that the meta-algorithm in a randomly generated graphs environment required up to 3 times less time to find a solution in a certain range of graphs than the best known general type algorithm, and was never slower in other ranges.