Miracle Play Launches Beta Version of AI Agent Tournament Simulation Content ‘AI GRANPRIX’

 – Leading Web3 Gaming Innovation through AI-based Esports Content

KINGSTOWN, Saint Vincent and the Grenadines, April 08, 2025 (GLOBE NEWSWIRE) — Miracle Play, a Web3 Esports tournament platform, officially launched the beta version of ‘AI GRANPRIX’, an AI agent racing simulation, on March 31.

‘AI GRANPRIX’ is designed as an autonomous simulation tournament system where AI agents learn racing strategies and compete based on user-created dNFT vehicles, offering an immersive experience distinct from traditional manual competition formats.

In this beta version, users mint dNFT vehicles based on custom basic stat distributions and directly observe how these stats influence simulated racing outcomes. Tournament results are presented as simulation replay videos derived from match data, providing immersive, spectator-focused Esports content for both participants and general users. A reinforcement learning mode for AI parameters will be gradually introduced starting early May. The official release will feature a fully operational technical framework in which AI’s strategic learning logic and match performance are interconnected in real-time.

Through this system, players assume a supervisory role, strategically influencing AI development and parameter optimization without direct manual operation. Achievements in reinforcement learning directly reflect in match performance, immediately linking match outcomes to the value of dNFT assets on-chain.

This creates a quantifiable cause-and-effect relationship between AI parameter optimization and match results, transforming players from mere consumers into designers and contributors who actively participate in asset value creation.

Such a structure establishes a clear feedback loop—”AI learning → Match results → On-chain asset appreciation”—highlighting Miracle Play’s realization of next-generation Esports architecture that organically connects AI technology with blockchain-based asset economies.

Additionally, Miracle Play’s tournament system introduces a novel GameFi model known as the “performance-based farming structure,” which transcends simple match participation. Players achieving above-average scores in tournaments receive gaming tokens as rewards, which can then be burned to secure reward shares. The more tokens a player burns, the higher their reward from the Burn Pool, thus incentivizing active participation and contributions simultaneously.

Within the community, this unique model has earned Miracle Play the nickname “Web3 Tournament Mining Machine,” creating a strategic mining meta. Because rewards depend not only on match outcomes but also on performance metrics and burn contributions, strategic data-driven participation and active contributions rather than mere luck become critical factors. This ecosystem is designed to seamlessly integrate play and farming, enhancing both on-chain economies and gameplay to deliver an active, reward-oriented Web3 gaming experience favored by MZ generation users.

Currently, Miracle Play boasts over 1.2 million cumulative tournament participants, total prize money of $350,000, and more than 2.8 million on-chain transactions, maintaining steady growth. Going forward, Miracle Play plans to open its proprietary technology ecosystem by introducing the ‘Miracle Agent SDK’ to external game developers. This initiative will facilitate easy integration of AI-based automated tournament systems across various game genres, accelerating the establishment of a universal Esports ecosystem combining AI technology and blockchain infrastructure.

A representative from Miracle Play stated, “AI GRANPRIX represents the first Esports model that integrates strategic AI learning, blockchain-based transparent competition structures, and digital asset mechanisms. We will continue refining the system based on user feedback and establish foundations for more games to implement AI-based tournaments through the Miracle Agent SDK.”

Contact:
Miracle Play
eight@miracleplay.gg

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