Multiuser online game with AI

• Main Author: Siew, Jun Leong
• Other Authors: Chua Hock Chuan
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/148929
• Institution: Nanyang Technological University

Games are played for many reasons. It can be a platform for social interaction, a way to challenge oneself, or just to escape reality [1]. Many games have a learning curve and logical reasoning is usually required. Any opponents or enemies in a game are usually hardcoded, thus they will be unable to match a human player since they operating within limited and specific parameters. With the introduction of newer deep reinforcement learning (RL) algorithms, Artificial Intelligence (AI) will now do more than ever before, whether it was playing a dynamic game like Dota or auto-generation of coherent images from partial images, AI succeeded in all of these. Without any experience in doing AI, it will be a great learning experience to be able to train an AI for a strategic game without hardcoding it. Thus the objective of the project is to build a imperfect information, multiuser online game integrated with AI. Through this project, an AI was trained with a promising level of proficiency using the Unity ML agent package, which simplifies the process of RL for a person who does not have much knowledge about AI and its training, but yet able to use an algorithm to train an RL AI for their purposes. If AI can be trained to human-like proficiency with such a simplified interface, it will open up a whole avenue for the future of games.