mlsanityData to 14 Oct 2026

Decentralized Intelligence in GameFi: Embodied AI Agents and the Convergence of DeFi and Virtual Ecosystems

arXiv 2412.18601 ↗First posted 24 Dec 2024cs.CR cs.AI cs.GTcited by 2

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

In the rapidly evolving landscape of GameFi, a fusion of gaming and decentralized finance (DeFi), there exists a critical need to enhance player engagement and economic interaction within gaming ecosystems. Our GameFi ecosystem aims to fundamentally transform this landscape by integrating advanced embodied AI agents into GameFi platforms. These AI agents, developed using cutting-edge large language models (LLMs), such as GPT-4 and Claude AI, are capable of proactive, adaptive, and contextually rich interactions with players. By going beyond traditional scripted responses, these agents become integral participants in the game's narrative and economic systems, directly influencing player strategies and in-game economies. We address the limitations of current GameFi platforms, which often lack immersive AI interactions and mechanisms for community engagement or creator monetization. Through the deep integration of AI agents with blockchain technology, we establish a consensus-driven, decentralized GameFi ecosystem. This ecosystem empowers creators to monetize their contributions and fosters democratic collaboration among players and creators. Furthermore, by embedding DeFi mechanisms into the gaming experience, we enhance economic participation and provide new opportunities for financial interactions within the game. Our approach enhances player immersion and retention and advances the GameFi ecosystem by bridging traditional gaming with Web3 technologies. By integrating sophisticated AI and DeFi elements, we contribute to the development of more engaging, economically robust, and community-centric gaming environments. This project represents a significant advancement in the state-of-the-art in GameFi, offering insights and methodologies that can be applied throughout the gaming industry.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 5 of its 25 references that are in the map. First posted on arXiv 24 Dec 2024.

Builds on

5 of 25 references.

References · 5

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2019Habitat: A Platform for Embodied AI Researchcited by 1,191
  3. 2019An analysis of Uniswap marketscited by 12
  4. 2021An Empirical Study of DeFi Liquidations: Incentives, Risks, and Instabilitiescited by 8
  5. 2019DECO: Liberating Web Data Using Decentralized Oracles for TLScited by 7

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

Similar, not cited

Close in wording, no citation either way

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  4. 2026EpochX: Building the Infrastructure for an Emergent Agent Civilization
  5. 2026Economy of Minds: Emerging Multi-Agent Intelligence with Economic Interactions
  6. 2026AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games
  7. 2025DAO-AI: Evaluating Collective Decision-Making through Agentic AI in Decentralized Governance
  8. 2025Can We Govern the Agent-to-Agent Economy?