New Metaverse Games Based on Artificial Intelligence: A Review

Abstract

The current review conveys Metaverse integration with AI-based gaming exploring the advancements in Metaverse games and its potential in growing self-learning AI in the latest years for the readers. Using state-of-the-art deep learning techniques, it aimed to pinpoint its advancements, issues, and suggested solutions. For the current review, 18 papers were used that appeared in peer-reviewed publications and were searchable on Google Scholar within the last five years (2020–2024). To analyse the collected data, thematic analysis was employed. The article delves into the various ways the Meta-Metaverse might be used in the gaming industry. It highlights how it can enhance character creation, game design, level design, and visual effects, among other areas. The entertainment industry’s usage of AI in game production encompasses a wide range of methods, such as CVEs, deep learning, and intrinsic curiosity-driven variation autoencoders.). The Metaverse, a dynamic platform, uses ML/DL algorithms for classification, clustering, and regression, while pre-trained AI models can achieve great responses quickly. These technologies streamline the gaming world and create interactive platforms for various applications. Deep Reinforcement Learning (DRL) is proposed as a dynamic solution to balance the stability of the game world, the intelligence of non-player characters, and the sustainability of the Metaverse environment.