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I don't currently have much practical experience with DQN, but I can partially answer this question also based on my theoretical knowledge and other info that I found. DQN is typically used for discrete action spaces (although there have been attempts to apply it to continuous action spaces, such as this one) discrete and continuous state spaces problems ...


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I could give you my $0.02 on fraud detection. Read everything you can on the Equifax breach and seek to secure your data Benfords Law would be a good place to start If you can isolate log activity that is inhumanly consistant, if you "ip_address", "id" and/or "timestamp" all show a constant 3 second gap between activity or its ...


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Specially on the problems related with PDEs you can find a relatively new article that is using a new approach to solve complex problems and improving the performance of classical approach. Examples arise in molecular dynamics, micro-mechanics, and turbulent flows. You can find the paper called: Fourier Neural Operator for Parametric PDEs from a recent ...


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James Ryan has done a lot of 'archaeological' work on this; you can find references to his work on his website. Story generation has been a dream for a long time (in computing terms), and various genres have been explored, with not that much success. There have been episodes of a Western written by a computer (and actually filmed and acted out by human ...


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Reinforcement learning (and, in particular, bandit) algorithms have been and can be used to solve problems other than games, such as Recommender systems (actually used in practice by e.g. Netflix or Microsoft) Portfolio optimization Clinical trials Hyper-parameter optimization Self-driving cars (although I am not aware of any real self-driving car that uses ...


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