Presentation 2012-09-21
Utilization of Reinforcement Learning for Broadcast Transmission in Inter-Vehicle Communication
Shinichiro MURATA, Takuji TACHIBANA,
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Abstract(in English) In broadcast transmission for inter-vehicle communication, a vehicle that sensed an event broadcasts sensing information to the vehicle behind. However, by using existing methods, the amount of data each vehicle receives depends on the road conditions. For example, a lot of data is transmitted to a vehicle redundantly or a vehicle cannot receive any data. In this paper, in order for each vehicle to receive the pre-decided number of data for inter vehicle communication, we propose a broadcast transmission with reinforcement learning. Here, the target number of data is set for each vehicle, and the vehicle obtains rewards based on the action. Then, the vehicle learns the optical action so that the maximum rewards can be obtained. Finally, each vehicle preforms the optimal action. We evaluate the performance of our proposed method. In numerical example, we show the effectiveness of the proposed method.
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Keyword(in English) VANET / Reinforcement learning / Broadcast / Q-learning / Reward function
Paper # NS2012-68
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Committee NS
Conference Date 2012/9/13(1days)
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Registration To Network Systems(NS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Utilization of Reinforcement Learning for Broadcast Transmission in Inter-Vehicle Communication
Sub Title (in English)
Keyword(1) VANET
Keyword(2) Reinforcement learning
Keyword(3) Broadcast
Keyword(4) Q-learning
Keyword(5) Reward function
1st Author's Name Shinichiro MURATA
1st Author's Affiliation Graduate School of Engineering University of Fukui()
2nd Author's Name Takuji TACHIBANA
2nd Author's Affiliation Graduate School of Engineering University of Fukui
Date 2012-09-21
Paper # NS2012-68
Volume (vol) vol.112
Number (no) 208
Page pp.pp.-
#Pages 4
Date of Issue