Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Ant Colony Optimization
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
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The cooperative optimization is a newly discovered metaheuristic for solving difficult combinatorial optimization problems. It is inspired by the cooperation principle in social systems where individuals in a system often work together in a cooperative way to solve hard problems of a complexity beyond the capability of any individual in the system. Unlike any existing metaheuristics, it has a number of global optimality conditions so that the cooperative optimization algorithms know where to find global optima and when to stop searching. Furthermore, a cooperative optimization algorithm has a unique equilibrium and converges to it with an exponential rate regardless of initial conditions and perturbations. In solving real-world optimization problems, the cooperative optimization algorithms have often significantly outperformed state-of-the-art algorithms.