Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments

Sun, Yi, Gomez, Faustino, Schmidhuber, Juergen

arXiv.org Machine Learning 

To maximize its success, an AGI typically needs to explore its initially unknown world. Is there an optimal way of doing so? Here we derive an affirmative answer for a broad class of environments.

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