Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking

15 November 2020

Papers citing "Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking"

8 / 8 papers shown

Title
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library Wenzhang Liu Wenzhe Cai Kun Jiang Guangran Cheng Yuanda Wang Changyin Sun Jingyu Cao Lele Xu Chaoxu Mu Changyin Sun 39 4 0 25 Dec 2023
Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models Pierre Schumacher Thomas Geijtenbeek Vittorio Caggiano Vikash Kumar Syn Schmitt Georg Martius Daniel Haeufle OOD OffRL 47 9 0 06 Sep 2023
Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems Junmin Zhong Ruofan Wu J. Si LRM 30 0 0 10 Oct 2022
Continuous MDP Homomorphisms and Homomorphic Policy Gradient S. Rezaei-Shoshtari Rosie Zhao Prakash Panangaden David Meger Doina Precup 35 18 0 15 Sep 2022
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems Pierre Schumacher Daniel Haeufle Le Chen Syn Schmitt Georg Martius 36 31 0 30 May 2022
Neural Circuit Architectural Priors for Embodied Control Nikhil X. Bhattasali A. Zador Tatiana A. Engel 88 5 0 13 Jan 2022
d3rlpy: An Offline Deep Reinforcement Learning Library Takuma Seno M. Imai OffRL GP 65 100 0 06 Nov 2021
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies Tim Seyde Igor Gilitschenski Wilko Schwarting Bartolomeo Stellato Martin Riedmiller Markus Wulfmeier Daniela Rus 28 44 0 03 Nov 2021