dotRL: A platform for rapid Reinforcement Learning methods development and validation
By Bartosz Papis, Pawel Wawrzynski. 2013
6 citations recorded by the source corpus.
Subfields: Reinforcement Learning
How researchers see this paper
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In Reinforcement Learning
- Sergey Levine
- Pieter Abbeel
- Chelsea Finn
- Yan Duan
- Xi Chen
- Abhishek Gupta
- John Schulman
- Shixiang Shane Gu
Citations in the corpus
- Benchmarking Deep Reinforcement Learning for Continuous Control (2016, methodology): “Tdlearn (Dann et al., 2014) includes a 20-link pole balancing task, DotRL (Papis & Wawrzy´nski, 2013) includes a variable-DOF octopus arm and a 6-DOF planar cheetah model, PyBrain (Schaul et al., 2010) includes a 16-DOF humanoid robot with standing and jumping tasks, RoboCup Keepaway (Stone et al.,…”
- RLLib: C++ Library to Predict, Control, and Represent Learnable Knowledge Using On/Off Policy Reinforcement Learning (2015, unknown): “dotRL[18] is a .”