Exploration of Game Artificial Intelligence: Key Technologies and Case Analysis

Yang Meng

2024

Abstract

Artificial Intelligence (AI) has seen rapid advancements in recent years, with game AI emerging as a key area for testing and refining AI technologies. Games have become valuable platforms for evaluating AI performance, exemplified by notable successes like AlphaGo and OpenAI's Dota 2 bots. This paper provides a comprehensive review of game AI development, focusing on the background and significance of game-based AI research. The paper is structured to: 1) introduce the foundations of game AI; 2) highlight the key characteristics of games used for AI testing; 3) present core algorithms such as Evolutionary Strategies (ES), Reinforcement Learning (RL), and Monte Carlo Tree Search (MCTS), detailing their basic principles; 4) discuss the practical applications of these algorithms in various games; 5) analyze the strengths and limitations of these techniques. Furthermore, the paper outlines the historical progression of game AI, its broader significance, and identifies the challenges and potential future research directions in this field. The goal is to offer beginners a clear understanding of game AI, while motivating deeper exploration of its technical complexities. Future work will delve into detailed studies of specific algorithms, expanding on their implementation and practical relevance.

Paper Citation

in Harvard Style

Meng Y. (2024). Exploration of Game Artificial Intelligence: Key Technologies and Case Analysis. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 349-353. DOI: 10.5220/0013517500004619

in Bibtex Style

@conference{daml24,
author={Yang Meng},
title={Exploration of Game Artificial Intelligence: Key Technologies and Case Analysis},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={349-353},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013517500004619},
isbn={978-989-758-754-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Exploration of Game Artificial Intelligence: Key Technologies and Case Analysis
SN - 978-989-758-754-2
AU - Meng Y.
PY - 2024
SP - 349
EP - 353
DO - 10.5220/0013517500004619
PB - SciTePress