Neural Game Engine: Accurate learning of generalizable forward models from pixels

23 Mar 2020Chris BamfordSimon Lucas

Access to a fast and easily copied forward model of a game is essential for model-based reinforcement learning and for algorithms such as Monte Carlo tree search, and is also beneficial as a source of unlimited experience data for model-free algorithms. Learning forward models is an interesting and important challenge in order to address problems where a model is not available... (read more)

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