The Use of Reinforcement Learning Algorithms in Traffic Control of High Speed Networks
Advances in Computational Intelligence and Learning: Methods and Applications
International Journal of Communication Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Parameter learning from stochastic teachers and stochastic compulsive liars
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hierarchical learning scheme for solving the stochastic point location problem
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Hi-index | 0.00 |
A novel algorithm named Adaptive Step Searching (ASS) is presented in the paper to solve the stochastic point location (SPL) problem. In the conventional method [1] for the SPL problem, the tradeoff between the convergence speed and accuracy is the main issue since the searching step of learning machine (LM) in the method is invariable during the entire searching. In that case, in ASS, LM adapts the step size to different situations during the searching. The convergence speed has been improved significantly with the same accuracy comparing to previous algorithms.