Intelligent-based multi-robot path planning inspired by improved classical Q-learning and improved particle swarm optimization with perturbed velocity
Classical Q-learning takes huge computation to calculate the Q-value for all possible actions in a particular state and takes large space to store its Q-value for all actions, as a result of which its convergence rate is slow. This paper proposed a new methodology to determine the optimize trajector...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2016-03-01
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| Series: | Engineering Science and Technology, an International Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215098615001548 |