A C++ template-based reinforcement learning library: fitting the code to the mathematics. This paper introduces the rllib as an original C++ template-based library oriented toward value function estimation. Generic programming is promoted here as a way of having a good fit between the mathematics of reinforcement learning and their implementation in a library. The main concepts of rllib are presented, as well as a short example.
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References in zbMATH (referenced in 2 articles )
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- Geramifard, Alborz; Dann, Christoph; Klein, Robert H.; Dabney, William; How, Jonathan P.: RLPy: a value-function-based reinforcement learning framework for education and research (2015)
- Frezza-Buet, Hervé; Geist, Matthieu: A C++ template-based reinforcement learning library: fitting the code to the mathematics (2013)