Explainable artificial intelligence (XAI) twin systems will be a fundamental
enabler of zero-touch network and service management (ZSM) for sixth-generation
(6G) wireless networks. A reliable XAI twin system for ZSM requires two
composites: an extreme analytical ability for discretizing the physical
behavior of the Internet of Everything (IoE) and rigorous methods for
characterizing the reasoning of such behavior. In this paper, a novel
neuro-symbolic explainable artificial intelligence twin framework is proposed
to enable trustworthy ZSM for a wireless IoE. The physical space of the XAI
twin executes a neural-network-driven multivariate regression to capture the
time-dependent wireless IoE environment while determining unconscious decisions
of IoE service aggregation. Subsequently, the virtual space of the XAI twin
constructs a directed acyclic graph (DAG)-based Bayesian network that can infer
a symbolic reasoning score over unconscious decisions through a first-order
probabilistic language model. Furthermore, a Bayesian multi-arm bandits-based
learning problem is proposed for reducing the gap between the expected
explained score and the current obtained score of the proposed neuro-symbolic
XAI twin. To address the challenges of extensible, modular, and stateless
management functions in ZSM, the proposed neuro-symbolic XAI twin framework
consists of two learning systems: 1) an implicit learner that acts as an
unconscious learner in physical space, and 2) an explicit leaner that can
exploit symbolic reasoning based on implicit learner decisions and prior
evidence. Experimental results show that the proposed neuro-symbolic XAI twin
can achieve around 96.26% accuracy while guaranteeing from 18% to 44% more
trust score in terms of reasoning and closed-loop automation.

本文提出了一种基于神经符号的可解释人工智能双胞胎框架，以实现对于无线万物互联环境下网络和服务管理的可靠信任，该框架通过神经网络驱动的多元回归捕捉时间相关的无线万物互联环境，并通过基于有向无环图的贝叶斯网络对无意识决策进行符号推理，实现了对显式学习者和隐式学习者的管理。实验结果表明，所提出的神经语义 XAI 双胞胎在理性和闭环自动化方面可实现约 96.26％的准确性，并保证了 18％到 44％的更多信任分数。

神经符号可解释的人工智能双胞胎用于无触碰 IoE 的无线网络

Neuro-symbolic Explainable Artificial Intelligence Twin for Zero-touch IoE in Wireless Network

The current prominence and future promises of the Internet of Things (IoT),
Internet of Everything (IoE) and Internet of Nano Things (IoNT) are extensively
reviewed and a summary survey report is presented. The analysis clearly
distinguishes between IoT and IoE which are wrongly considered to be the same
by many people. Upon examining the current advancement in the fields of IoT,
IoE and IoNT, the paper presents scenarios for the possible future expansion of
their applications.

本文介绍了物联网（IoT）、一切互联（IoE）和纳米物联网（IoNT）的当前地位和未来前景，并对其应用现状和可能的扩展进行了分析和总结。