Gaming, Goats & General Intelligence with Frederic Besse
Google DeepMind: The Podcast
Evolution of AI in Gaming
This chapter examines the transition from traditional game agents to modern deep learning agents, highlighting key milestones in AI advancements, such as the DQN and AlphaGo. It also explores the complexities of training agents in dynamic environments, emphasizing the importance of reinforcement learning and imitation learning. Through various examples, including innovative projects like CIMA and interactions in simulated worlds, the chapter illustrates the challenges and creativity involved in developing versatile AI for gaming.
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