Abstract
Intelligent models of random walk are obtained from random walk algorithms and a learning element. In this chapter, the learning element is a type of learning automata which is called as variable-structure learning automata. In this chapter, this type of learning automata is used to design three intelligent models of random walk. The first model is called Intelligent K-Random Walk based on Learning Automata (IKRW-LA). This model is able to predict k promising links from each arbitrary node in the networks. The second model is called Self-Organized Intelligent Random Walk based on Learning Automata (SOIRW-LA). This model is proposed to add the learning capability to k-random walk for path prediction. In this model, we do not need to determine the value for parameter k to find the promising links. The third model is called Intelligent Random Walk based on Learning Automata (IRW-LA). The advantage of this model than the others models is to predict the best path of the network considering the feedback received from the network. This model is equivalent to the first model (IKRW-LA) when the value of parameter k is equal to one. The convergence behavior of the IRW-LA is also studied. All of the mentioned models are described in this chapter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Linear Reward Penalty.
- 2.
Linear Reward Epsilon Penalty.
- 3.
Linear Reward Inaction.
References
Narendra KS, Thathachar MA (1989) Learning automata: an introduction. Prentice-Hall
Abolhassani M, Esnaashari M, Meybodi MR (2009) LADIT: A learning automata fault tolerant routing protocol for sensor networks. Yazd, Iran, pp 12–18
Rezvanian A, Saghiri AM, Vahidipour M, Esnaashari M, Meybodi MR (2018) Recent advances in learning automata. Springer
Akbari Torkestani J, Meybodi MR (2010) Mobility-based multicast routing algorithm for wireless mobile Ad-hoc networks: a learning automata approach. Comput Commun 33:721–735
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Saghiri, A.M., Khomami, M.D., Meybodi, M.R. (2019). Intelligent Models of Random Walk. In: Intelligent Random Walk: An Approach Based on Learning Automata. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-030-10883-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-10883-0_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-10882-3
Online ISBN: 978-3-030-10883-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)