Metaversal intelligence: Unifying human-AI interactions in human-in-the-loop AIB-Metaverse

IF 4.6 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Networks Pub Date : 2025-06-04 DOI:10.1016/j.comnet.2025.111425

Minoo Soltanshahi, Martin Maier

{"title":"Metaversal intelligence: Unifying human-AI interactions in human-in-the-loop AIB-Metaverse","authors":"Minoo Soltanshahi, Martin Maier","doi":"10.1016/j.comnet.2025.111425","DOIUrl":null,"url":null,"abstract":"<div><div>The convergence of 6G and Web 3 technologies with the Metaverse necessitates user-centric, intelligent solutions to address challenges of adaptability, scalability, and efficiency in decentralized systems. This paper introduces the Human-AI Blockchain (HAIB) Metaverse architecture and the Intelligent Smart Contract (InSC) framework, which integrate Reinforcement Learning (RL) and extended stigmergy to optimize multi-agent interactions and enable dynamic, self-executing smart contracts. The HAIB architecture enhances human-AI collaboration through a human-in-the-loop approach, facilitating adaptive decision-making and efficient resource allocation. Serving as the cognitive core, the InSC framework combines dynamic environmental feedback with real-time data analytics to enable intelligent decision-making. Experimental evaluations demonstrate that the proposed framework reduces gas consumption by 32–33% while increasing cumulative rewards. These findings highlight the significant potential of intelligent smart contracts in advancing decentralized intelligence within the Metaverse.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111425"},"PeriodicalIF":4.6000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389128625003925","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}

引用次数: 0

Abstract

The convergence of 6G and Web 3 technologies with the Metaverse necessitates user-centric, intelligent solutions to address challenges of adaptability, scalability, and efficiency in decentralized systems. This paper introduces the Human-AI Blockchain (HAIB) Metaverse architecture and the Intelligent Smart Contract (InSC) framework, which integrate Reinforcement Learning (RL) and extended stigmergy to optimize multi-agent interactions and enable dynamic, self-executing smart contracts. The HAIB architecture enhances human-AI collaboration through a human-in-the-loop approach, facilitating adaptive decision-making and efficient resource allocation. Serving as the cognitive core, the InSC framework combines dynamic environmental feedback with real-time data analytics to enable intelligent decision-making. Experimental evaluations demonstrate that the proposed framework reduces gas consumption by 32–33% while increasing cumulative rewards. These findings highlight the significant potential of intelligent smart contracts in advancing decentralized intelligence within the Metaverse.

查看原文本刊更多论文

元宇宙智能：在人在环aib -元宇宙中统一人类与ai的交互

6G和Web 3技术与Metaverse的融合需要以用户为中心的智能解决方案，以应对分散系统中适应性、可扩展性和效率方面的挑战。本文介绍了Human-AI b区块链（HAIB）元宇宙架构和智能智能合约（InSC）框架，该框架集成了强化学习（RL）和扩展stigmergy，以优化多代理交互并启用动态、自执行的智能合约。HAIB架构通过人在循环的方法增强了人类与人工智能的协作，促进了适应性决策和有效的资源分配。作为认知核心，InSC框架将动态环境反馈与实时数据分析相结合，从而实现智能决策。实验评估表明，该框架减少了32-33%的天然气消耗，同时增加了累积奖励。这些发现突出了智能合约在推进元宇宙中去中心化智能方面的巨大潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Computer Networks 工程技术-电信学

CiteScore

10.80

自引率

3.60%

发文量

434

审稿时长

8.6 months

期刊介绍： Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.