NDLI: Cooperation in wireless networks: a game-theoretic framework with reinforcement learning

Content Provider	IET Digital Library
Author	Baidas, Mohammed Wael
Abstract	A game-theoretic framework based on the iterated prisoner's dilemma (IPD) is proposed to model the repeated dynamic interactions of multiple source nodes when communicating with multiple destinations in an ad hoc wireless network. In such networks where nodes are autonomous, selfish and not familiar with other nodes’ strategies, fully cooperative behaviours cannot be assumed. Therefore reinforcement learning is studied to relate the utility function of each source node to actions previously taken in order to learn a strategy that maximises their expected future reward. Particularly, a Q-learning algorithm is proposed to allow network nodes to adapt to and play the IPD game against opponents with a variety of known and unknown strategies. Simulation results illustrate that the proposed Q-learning algorithm allows network nodes to play optimally and achieve their maximum expected return values.
Starting Page	740
Ending Page	753
Page Count	14
ISSN	17518628
Volume Number	8
e-ISSN	17518636
Issue Number	Issue 5, Mar (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/8/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2013.0817
Journal	IET Communications
Publisher Date	2014-02-05
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Ad Hoc Network Ad Hoc Wireless Network Communication Computing Cooperation Communication Cooperative Communication Game Theory Interpolation And Function Approximation IPD Game Iterated Prisoner Dilemma Iterative Method Knowledge Engineering Technique Learning in AI Maximum Expected Return Value Network Node Numerical Analysis Q-learning Algorithm Radio Link And Equipment Reinforcement Learning Repeated Dynamic Interaction Source Node Utility Function
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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