Tlili, A.; Chikhi, S. Optimization of Greedy Randomized Adaptive Search Procedure. Preprints2024, 2024010056. https://doi.org/10.20944/preprints202401.0056.v1
APA Style
Tlili, A., & Chikhi, S. (2024). Optimization of Greedy Randomized Adaptive Search Procedure. Preprints. https://doi.org/10.20944/preprints202401.0056.v1
Chicago/Turabian Style
Tlili, A. and Salim Chikhi. 2024 "Optimization of Greedy Randomized Adaptive Search Procedure" Preprints. https://doi.org/10.20944/preprints202401.0056.v1
Abstract
Although the behavioral mechanism studying is a difficult and complex task, it can produce an important systems optimization impact. In this work, we use, in this paper, inference system approach to represent reasoning mechanism and the operations of dynamic systems to extract mental representations from traveling salesman and convert them into cognitive structures. For this we develop an extraction automatic method to create knowledge bases and, later, data are stocked into structure based on transition maps and the performances of these created maps get improved through combining the reinforcement learning thus augment traveller's deciding capacity from historical data. These transition maps help to find best actions for obtaining useful new policies. Generated intermediate transition maps are gathered to give a global map called main map whose advantage is to improve the learning process. The main idea of this approach is to improve learning capability by using a reinforcement learning technique as exploration and exploitation strategy of the metaheuristique GRASP method and the use of the fuzze logical rules mechanism allowing concepts model to have more variability of states. The results obtained after simulation as presented in this paper are very encouraging.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
