|International Conference on Recent Trends in Science, Technology, Management and Social Development
|Foundation of Computer Science USA
|ICRTSTMSD2018 - Number 1
|Authors: Manan Kalra, J. C. Patni
Manan Kalra, J. C. Patni . Playing Doom with Deep Reinforcement Learning. International Conference on Recent Trends in Science, Technology, Management and Social Development. ICRTSTMSD2018, 1 (August 2019), 14-20.
In this work, we present a deep learning model based on reinforcement learning that is tied to an AI agent. The agent successfully learns policies to control itself in a virtual game environment directly from high-dimensional sensory inputs. The model is a convolutional neural network, trained with a variant of the Q-learning algorithm, whose input is raw pixels and whose output is a Q-value directly associated with the best possible future action. We apply our method to a first-person shooting game - Doom. We find that it outperforms all previous approaches and also surpasses a human expert.