Comparing Knowledge-based Reinforcement Learning to Neural Networks in a Strategy Game

15 Jan 2019Liudmyla NechepurenkoViktor VossVyacheslav Gritsenko

The paper reports on an experiment, in which a Knowledge-Based Reinforcement Learning (KB-RL) method was compared to a Neural Network (NN) approach in solving a classical Artificial Intelligence (AI) task. In contrast to NNs, which require a substantial amount of data to learn a good policy, the KB-RL method seeks to encode human knowledge into the solution, considerably reducing the amount of data needed for a good policy... (read more)

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