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I. INTRODUCTION

II. BACKGROUND
A. Deep learning
B. Reinforcement learning

III. DEEP REINFORCEMENT LEARNING
A. Value-based DRL methods
B. Policy gradient DRL methods
C. Model-based DRL methods

IV. DRL IN VIDEO GAMES
A. Game research platforms
B. Atari games
C. First-person perspective games
D. Real-time strategy games

V. CHALLENGES IN GAMES WITH DRL
A. Exploration-exploitation
B. Sample efficiency
C. Generalization and Transfer
D. Multi-agent learning
E. Imperfect information
F. Delayed spare rewards

VI. CONCLUSION AND DISCUSSION
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