AIBullisharXiv – CS AI · 14h ago6/10
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Enhancing Reinforcement Learning in 3D Environments through Semantic Segmentation: A Case Study in ViZDoom
Researchers propose semantic segmentation-based input representations to address memory and learning challenges in reinforcement learning for 3D environments, demonstrating 66-98% memory reduction in ViZDoom experiments while improving agent performance through enhanced visual information processing.