Implements reinforcement learning environments and algorithms as described in Sutton & Barto (1998, ISBN:0262193981). The Q-Learning algorithm can be used with different types of function approximation (tabular and neural network), eligibility traces (Singh & Sutton (1996) <doi:10.1007/BF00114726>) and experience replay (Mnih et al. (2013) <arXiv:1312.5602>).
|Author||Markus Dumke [aut, cre]|
|Maintainer||Markus Dumke <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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