13Q Learning Algorithm for Network Resource Management in Vehicular Communication Network
Vartika Agarwal* and Sachin Sharma
Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, Uttarakhand, India
Abstract
Q learning is a machine learning technique which is used in vehicular communication network. It provides faster communication between vehicles. In this paper, we reviewed various algorithms such as value based, policy based, Model based, Q-learning based algorithm used for reinforcement learning. We highlight working of an agent, importance, applications and terminologies of Q learning. This chapter helps researchers to find out the research gap for further research.
Keywords: Vehicular Communication Network (VCN), Reinforcement Learning (RL), Q Learning, Machine learning
13.1 Introduction
Q learning is a kind of machine learning method. In this algorithm, there would be an agent which interacts with a specific environment. Firstly, the agent will try to interact with the environment and then after observing the environment, an agent will have to take necessary actions according to the current state of an environment.
Following are the steps of Q learning methods:
- Firstly we have to train an agent so that it can interact with a specific environment.
- Observe the current situation of an environment.
- Make strategies regarding current state of an environment and perform relevant action.
- Now, an agent can get corresponding reward ...
Get Autonomous Vehicles, Volume 2 now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.