Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Local search techniques have been applied in optimization methods. The effect of local search to the memetic algorithms can make multimodal and non-linear problems easier to solve...
The paper considers the consensus problem in a partially synchronous system with Byzantine faults. It turns out that, in the partially synchronous system, all deterministic algorit...
Planning is an artificial intelligence problem with a wide range of real-world applications. Genetic algorithms, neural networks, and simulated annealing are heuristic search met...
Han Yu, Dan C. Marinescu, Annie S. Wu, Howard Jay ...
A new computational paradigm is described which o ers the possibility of superlinear and sometimes unbounded speedup, when parallel computation is used. The computations involved ...