Evaluating the impact of curriculum learning on the training process for an intelligent agent in a video game

Abstract

We want to measure the impact of the curriculum learning technique on a reinforcement training setup, several experiments were designed with different training curriculums adapted for the video game chosen as a case study. Then all were executed on a selected game simulation platform, using two reinforcement learning algorithms, and using the mean cumulative reward as a performance measure. Results suggest that curriculum learning has a significant impact on the training process, increasing training times in some cases, and decreasing them up to 40% percent in some other cases.

Keywords

• Curriculum Learning
• Game AI
• Unity Machine Learning Agents
• Training Curriculum
• Mean Cumulative Reward
• Proximal Policy Optimization