Reinforcement Learning
Overview
Implements reinforcement learning environments and algorithms as described in Sutton & Barto (1998, ISBN:0262193981). The Q-Learning algorithm can be used with function approximation, eligibility traces (Singh & Sutton (1996) doi:10.1007/BF00114726) and experience replay (Mnih et al. (2013) arXiv:1312.5602).
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Health
CRAN check results are not tracked yet.
Documentation
- Help pages
- 28includes a package overview page
- Examples that run
- 91%21 run in a plain check · 2 never run
- Exported functions with examples
- 82%
- Documented parameters
- 100%
- Return-value docs
- 45%
- Help pages citing references
- 11%
Downloads
Dependencies
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.1.0 released · 2021-05-18
- archivedRemoved from CRAN2021-01-10check problems were not corrected in time
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- unarchivedReturned to CRAN2019-04-09
- 0.2.12019-04-09 · diff ↗
- archivedRemoved from CRAN2019-04-08failed its check with current R, despite reminder
- 0.2.02019-03-20 · diff ↗
- RR 3.5.0 released · 2018-04-23
- 0.1.02018-01-03
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2018-01-03
- Total releases
- 3 / 8 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.0.0
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