Improved Belgian AI Algorithm for Dynamic Management in Action Role-Playing Games

Author:

Mi QingweiORCID,Gao Tianhan

Abstract

Artificial intelligence in games is one of the most challenging tasks in academia and industry. In action role-playing games, how to manage combat effectively is a key issue related to game development and the player’s experience. The Belgian artificial intelligence (BAI) algorithm is a classic but limited method that is widely used for combat management between the player and enemies. To address the poor adaptability of BAI, this paper proposes an improved Belgian artificial intelligence (IBAI) algorithm with dynamic difficulty adjustment (DDA) and implements two systems separately based on BAI and IBAI in Unreal Engine 4. Advantages on 12 parameters—10.086 mean total score greater, and 0.079 standard deviation smaller—demonstrate that the system based on IBAI has higher adaptability and a better player experience by comparing the two systems in different situations and inviting players to participate in gameplay experiences and questionnaires. The robust dynamic management mechanism of IBAI can help game designers and developers achieve the combat system of action role-playing games more efficiently, thus, shortening the development cycle and improving the player retention rate.

Funder

China Fundamental Research Funds for the Central Universities

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Extending a MAPE-K loop-based framework for Dynamic Difficulty Adjustment in single-player games;Entertainment Computing;2025-01

2. DDA-MAPEKit: A Framework for Dynamic Difficulty Adjustment Based on MAPE-K Loop;Proceedings of the 22nd Brazilian Symposium on Games and Digital Entertainment;2023-11-06

3. Optimizing Real-Time Path Planning for NPC Navigation: Leveraging CentA* Algorithm to Enhance Efficiency and Adaptability;2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI);2023-10-19

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