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MemoryGame: Decentralized P2E Game for Visual Working Memory Training | IEEE Conference Publication | IEEE Xplore

MemoryGame: Decentralized P2E Game for Visual Working Memory Training


Abstract:

Visual Working Memory (VWM) is the ability to maintain task-relevant visual information over a brief delay after direct visual input has been removed and it is essential ...Show More

Abstract:

Visual Working Memory (VWM) is the ability to maintain task-relevant visual information over a brief delay after direct visual input has been removed and it is essential for learning new skills, solving tasks and acquiring new knowledge. In this paper, authors presented MemoryGame: a decentralized Play-to-Earn (P2E) games that aim to train VWM. Blockchain implementation will maintain player's privacy where they could play the game activities without sharing any personal information. Furthermore, MemoryGame applied P2E model to encourage player's engagement and maintain the sustainable retention rate.
Date of Conference: 05-07 June 2024
Date Added to IEEE Xplore: 11 July 2024
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Conference Location: Turin, Italy

References

References is not available for this document.