Exploring Deep Recurrent Q-Learning for Navigation in a 3D Environment
Rasmus Kongsmar Brejl, Henrik Purwins, Henrik Schoenau‐Fog · EAI Endorsed Transactions on Creative Technologies · 2018
Learning to navigate in 3D environments from raw sensory input is an important step towards bridging the gap between human players and artificial intelligence in digital games. Recent advances in deep reinforcement learning have seen success in teaching agents to play Atari 2600 games from raw pixel