Supplementary information for Bayesian reinforcement learning and Bayesian deep learning for blockchains with mobile edge computing

Article abstractWe present a novel game-theoretic, Bayesian reinforcement learning (RL) and deep learning (DL) framework to represent interactions of miners in public and consortium blockchains with mobile edge computing (MEC). Within the framework, we formulate a stochastic game played by miners un...

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Bibliographic Details

Main Authors:	Alia Asheralieva, Dusit Niyato
Format:	Data Data
Published:	2020
Subjects:	Communications engineering Cybersecurity and privacy Distributed computing and systems software Bayesian methods Blockchains Deep learning Game theory Incomplete information Machine learning Mobile edge computing Partially-observable Markov decision process Reinforcement learning Resource management
Online Access:	https://dx.doi.org/10.17028/rd.lboro.27204573.v1
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