meta-heuristics
Expanded definition
Meta-heuristics are high-level procedures or strategies designed to guide underlying heuristics toward a more effective search for solutions to complex optimization problems. They are particularly useful in scenarios where traditional optimization methods may fail due to the size or complexity of the search space. Common examples include genetic algorithms, simulated annealing, and tabu search.
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meta-heuristics FAQ
What is meta-heuristics?
A class of optimization algorithms that use iterative processes to find solutions.
How is meta-heuristics used in AI systems?
Meta-heuristics are high-level procedures or strategies designed to guide underlying heuristics toward a more effective search for solutions to complex optimization problems. They are particularly useful in scenarios where traditional optimization methods may fail due to the size or complexity of the search space. Common examples include genetic algorithms, simulated annealing, and tabu search.
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