most citedReproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

187 citations · 237 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL201719 cited

Learning Robust Dialog Policies in Noisy Environments

Maryam Fazel-Zarandi, Shang-Wen Li, Jin Cao +4

Modern virtual personal assistants provide a convenient interface for completing daily tasks via voice commands. An important consideration for these assistants is the ability to r…

cs.LG201714 cited

Bayesian Policy Gradients via Alpha Divergence Dropout Inference

Peter Henderson, Thang Doan, Riashat Islam +1

Policy gradient methods have had great success in solving continuous control tasks, yet the stochastic nature of such problems makes deterministic value estimation difficult. We pr…

cs.CL2017

Ethical Challenges in Data-Driven Dialogue Systems

Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier +4

The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent paradigm. A growing number of dialogue systems use conversation strategies that a…

cs.RO2017

Underwater Multi-Robot Convoying using Visual Tracking by Detection

Florian Shkurti, Wei-Di Chang, Peter Henderson +7

We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments. Our method…

cs.LG2017

OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning

Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon +3

Reinforcement learning has shown promise in learning policies that can solve complex problems. However, manually specifying a good reward function can be difficult, especially for…

cs.AI201717 cited

Benchmark Environments for Multitask Learning in Continuous Domains

Peter Henderson, Wei-Di Chang, Florian Shkurti +3

As demand drives systems to generalize to various domains and problems, the study of multitask, transfer and lifelong learning has become an increasingly important pursuit. In disc…