A Reinforcement Learning Integrated in Heuristic search method for self-driving vehicle using blockchain in supply chain management

被引：0

作者：

Nasurudeen Ahamed N. ^{[1
]}

Karthikeyan P. ^{[1
]}

机构：

[1] Presidency University, Bangalore

来源：

International Journal of Intelligent Networks | 2020年 / 1卷

关键词：

Artificial intelligence; Blockchain; Machine learning; Public ledger; Reinforcement learning; Self-driving;

D O I：

10.1016/j.ijin.2020.09.001

中图分类号：

学科分类号：

摘要：

Blockchain is a distributed open (Public) ledger that is used to record the transaction across many computers. Blockchain technology can be applied in any domain such as banking, healthcare, real estate, travel, food, and supply chain. In supply chain management to train the self-driving vehicle in blockchain technology also integrate the Artificial Intelligence (AI) and Machine Learning (ML) Algorithms. In this paper we have proposed Reinforcement learning integrated heuristic search method (RLIH) for self-driving vehicle using blockchain in supply chain management by combining the advantage of reinforcement learning and heuristic search method. RLIH is developed using Decentralized app and result shows that proposed method outperform the existing heuristic search method in term of service time and data traffic. © 2020 The Author(s)

引用

页码：92 / 101

页数：9