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The Optimal Path Finding Algorithm Based on Reinforcement Learning

The Optimal Path Finding Algorithm Based on Reinforcement Learning

Ganesh Khekare, Pushpneel Verma, Urvashi Dhanre, Seema Raut, Shahrukh Sheikh
Copyright: © 2020 |Volume: 12 |Issue: 4 |Pages: 18
ISSN: 1942-9045|EISSN: 1942-9037|EISBN13: 9781799806127|DOI: 10.4018/IJSSCI.2020100101
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MLA

Khekare, Ganesh, et al. "The Optimal Path Finding Algorithm Based on Reinforcement Learning." IJSSCI vol.12, no.4 2020: pp.1-18. http://doi.org/10.4018/IJSSCI.2020100101

APA

Khekare, G., Verma, P., Dhanre, U., Raut, S., & Sheikh, S. (2020). The Optimal Path Finding Algorithm Based on Reinforcement Learning. International Journal of Software Science and Computational Intelligence (IJSSCI), 12(4), 1-18. http://doi.org/10.4018/IJSSCI.2020100101

Chicago

Khekare, Ganesh, et al. "The Optimal Path Finding Algorithm Based on Reinforcement Learning," International Journal of Software Science and Computational Intelligence (IJSSCI) 12, no.4: 1-18. http://doi.org/10.4018/IJSSCI.2020100101

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Abstract

Urbanization has been extensively increased in the last decade. In proportion, the number of vehicles throughout the world is increasing broadly. The detailed survey of available optimal path algorithms is done in this article, and to ease the overall traveling process, a dynamic algorithm is proposed. The proposed algorithm takes into consideration multiple objectives like dynamic traffic density, distance, history data, etc. and provides an optimal route solution. It is hinged on reinforcement learning and capable of deciding the optimal route on its own. A comparative analysis of the proposed algorithm is done with a genetic algorithm, particle swarm optimization algorithm, and the artificial neural networks algorithm. Through simulation results, it is proved that the proposed algorithm has better efficiency, decision making, and stability. It will ease the driver's headache and make the journey more comfortable with traffic less short distance routes that will minimize overall travel time making a positive impact on traffic jams, accidents, fuel consumption, and pollution.

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