- For a more comprehensive survey about the multi-armed bandit problem, read A Survey of Online Experiment Design with Stochastic Multi-Armed Bandit: https://arxiv.org/pdf/1510.00757.pdf.
- For reading the paper that leverages intrinsic motivation for playing Montezuma's Revenge, refer to Unifying Count-Based Exploration and Intrinsic Motivation: https://arxiv.org/pdf/1606.01868.pdf.
- For the original ESBAS paper, follow this link: https://arxiv.org/pdf/1701.08810.pdf.
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You're reading from Reinforcement Learning Algorithms with Python
Andrea Lonza is a deep learning engineer with a great passion for artificial intelligence and a desire to create machines that act intelligently. He has acquired expert knowledge in reinforcement learning, natural language processing, and computer vision through academic and industrial machine learning projects. He has also participated in several Kaggle competitions, achieving high results. He is always looking for compelling challenges and loves to prove himself.
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Andrea Lonza is a deep learning engineer with a great passion for artificial intelligence and a desire to create machines that act intelligently. He has acquired expert knowledge in reinforcement learning, natural language processing, and computer vision through academic and industrial machine learning projects. He has also participated in several Kaggle competitions, achieving high results. He is always looking for compelling challenges and loves to prove himself.
Read more about Andrea Lonza