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- W3178763036 abstract "This paper presents a careful comparative analysis of two different reinforcement learning algorithms,An agent with specified coordinates in a gird based environment with obstacles calculates a route for it to travel using q-learning and sarsa.An individual componentTo solve optimization of energy in Pliug-in hybrid vehicles based on power demand by utilizing dynamic programming.The principle objective of the paper is to track down the ideal way and to recognize the Q-learning and SARSA calculations and furthermore streamlining the battery phev vehicle. These calculations utilize either the on-strategy or off-arrangement systems of support learning. For the on-approach technique, we have used the SARSA calculation and for the off-arrangement methodology, the Q-learning calculation has been used. These computations also affectingly affect tracking down the most short route possible for the robot" @default.
- W3178763036 created "2021-07-19" @default.
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- W3178763036 date "2021-07-01" @default.
- W3178763036 modified "2023-09-23" @default.
- W3178763036 title "Route Planning using Reinforcement Learning and Battery Optimization in Phev’s" @default.
- W3178763036 hasPublicationYear "2021" @default.
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