차량 네트워크의 강화학습 기반 자원 재할당 제어 방법에 관한 연구 Reinforcement learning based
resource Page 1 차량 네트워크의 강화학습 기반 자원 재할당 제어 방법에 관한 연구 이지훈, 오승은 …

요 약본 논문에서는 차량 간 통신에서 다양한 요구 조건을 만족하기 위해 심층강화학습을
사용하는 방안을제시한다. 심층강화학습 중 actor-critic 알고리즘을 활용해 주변 채널 상황을 …

요 약본 논문은 실시간으로 각 차량의 태스크를 주변 기지국에 할당하는 강화학습 기반 모델을
제안한다. 이 모델에서는 multi-agent 심층 강화학습 기반의 distributed resource allocation …

With the increasing demand of users for high-speed, low-delay and high-reliability services
in connected vehicles network, wireless networks with communication, caching and …

요 약 3GPP LTE C-V2X (Cellular Vehicle-to-Everything) mode 4 에서 SB-SPS (Sensing-
Based Semi-Persistent Scheduling) MAC (Medium Access Control) 에 의해 차량 단말 (VUE …

Vehicular networks have drawn many researchers' attention for the reason that vehicular
networks can change the operation of vehicles into a safer and greener state. Resource …

With the increasing attention to front-edge vehicular communication applications, distributed
resource allocation is beneficial to the direct communications between vehicle nodes …

Reinforcement learning is an area of machine learning that studies how an intelligent agent
takes actions in a given environment to maximize the cumulative reward. In this paper, we …

A Q-Learning based back-off algorithm was proposed in this paper because the traditional
DCF approach used for IEEE 802.11 p MAC protocol to access the channel has some …

With the rapid growth of computer vision applications, a large amount of video data in the
Internet of Vehicles scenario are used for content analysis. Tasks based on video content …