ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1709.06683
  4. Cited By
OptionGAN: Learning Joint Reward-Policy Options using Generative
  Adversarial Inverse Reinforcement Learning

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

20 September 2017
Peter Henderson
Wei-Di Chang
Pierre-Luc Bacon
David Meger
Joelle Pineau
Doina Precup
    GAN
ArXivPDFHTML

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

16 / 16 papers shown
Title
Imitation Learning with Additional Constraints on Motion Style using
  Parametric Bias
Imitation Learning with Additional Constraints on Motion Style using Parametric Bias
Kento Kawaharazuka
Yoichiro Kawamura
K. Okada
Masayuki Inaba
48
12
0
10 Jul 2024
Hierarchical Imitation Learning with Vector Quantized Models
Hierarchical Imitation Learning with Vector Quantized Models
Kalle Kujanpää
Joni Pajarinen
Alexander Ilin
27
12
0
30 Jan 2023
Divide & Conquer Imitation Learning
Divide & Conquer Imitation Learning
Alexandre Chenu
Nicolas Perrin-Gilbert
Olivier Sigaud
16
5
0
15 Apr 2022
Transfering Hierarchical Structure with Dual Meta Imitation Learning
Transfering Hierarchical Structure with Dual Meta Imitation Learning
Chongkai Gao
Yizhou Jiang
F. Chen
30
8
0
28 Jan 2022
Parallelized and Randomized Adversarial Imitation Learning for
  Safety-Critical Self-Driving Vehicles
Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehicles
Won Joon Yun
Myungjae Shin
Soyi Jung
S. Kwon
Joongheon Kim
27
5
0
26 Dec 2021
Learning from Guided Play: A Scheduled Hierarchical Approach for
  Improving Exploration in Adversarial Imitation Learning
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning
Trevor Ablett
Bryan Chan
Jonathan Kelly
37
4
0
16 Dec 2021
Recent Advances in Leveraging Human Guidance for Sequential
  Decision-Making Tasks
Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks
Ruohan Zhang
F. Torabi
Garrett A. Warnell
Peter Stone
86
28
0
13 Jul 2021
Online Baum-Welch algorithm for Hierarchical Imitation Learning
Online Baum-Welch algorithm for Hierarchical Imitation Learning
Vittorio Giammarino
I. Paschalidis
OffRL
22
2
0
22 Mar 2021
Learning from Suboptimal Demonstration via Self-Supervised Reward
  Regression
Learning from Suboptimal Demonstration via Self-Supervised Reward Regression
Letian Chen
Rohan R. Paleja
Matthew C. Gombolay
SSL
14
104
0
17 Oct 2020
Joint Goal and Strategy Inference across Heterogeneous Demonstrators via
  Reward Network Distillation
Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation
Letian Chen
Rohan R. Paleja
Muyleng Ghuy
Matthew C. Gombolay
27
38
0
02 Jan 2020
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single
  Observed Demonstration
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration
Brahma S. Pavse
F. Torabi
Josiah P. Hanna
Garrett A. Warnell
Peter Stone
27
33
0
18 Jun 2019
Recent Advances in Imitation Learning from Observation
Recent Advances in Imitation Learning from Observation
F. Torabi
Garrett A. Warnell
Peter Stone
23
163
0
30 May 2019
An Algorithmic Perspective on Imitation Learning
An Algorithmic Perspective on Imitation Learning
Takayuki Osa
Joni Pajarinen
Gerhard Neumann
J. Andrew Bagnell
Pieter Abbeel
Jan Peters
48
830
0
16 Nov 2018
Improving GAN Training via Binarized Representation Entropy (BRE)
  Regularization
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
Yanshuai Cao
G. Ding
Kry Yik-Chau Lui
Ruitong Huang
GAN
18
19
0
09 May 2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
Joshua Romoff
Peter Henderson
Alexandre Piché
Vincent François-Lavet
Joelle Pineau
13
42
0
09 May 2018
No Metrics Are Perfect: Adversarial Reward Learning for Visual
  Storytelling
No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling
Xin Eric Wang
Wenhu Chen
Yuan-fang Wang
William Yang Wang
16
157
0
24 Apr 2018
1