English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets

Hausman, K., Chebotar, Y., Schaal, S., Sukhatme, G., & Lim, J. (2018). Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets. In I. Guyon, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, & R. Garnett (Eds.), Advances in Neural Information Processing Systems 30 (pp. 1236-1246). Red Hook, NY: Curran Associates, Inc. Retrieved from https://papers.nips.cc/paper/6723-multi-modal-imitation-learning-from-unstructured-demonstrations-using-generative-adversarial-nets.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-0000-FEB5-6 Version Permalink: https://hdl.handle.net/21.11116/0000-000A-EB45-0
Genre: Conference Paper

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Hausman, Karol1, Author
Chebotar, Yevgen1, Author
Schaal, Stefan2, Author           
Sukhatme, Gaurav1, Author
Lim, Joseph1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Autonomous Motion, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497646              

Content

show
hide
Free keywords: Abt. Schaal
 Abstract: -

Details

show
hide
Language(s): eng - English
 Dates: 20172018-06
 Publication Status: Issued
 Pages: 11
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: intentiongan_nips17
URI: https://papers.nips.cc/paper/6723-multi-modal-imitation-learning-from-unstructured-demonstrations-using-generative-adversarial-nets
 Degree: -

Event

show
hide
Title: 31st Annual Conference on Neural Information Processing Systems (NIPS 2017)
Place of Event: Long Beach, CA
Start-/End Date: 2017-12-04 - 2017-12-09

Legal Case

show

Project information

show

Source 1

show
hide
Title: Advances in Neural Information Processing Systems 30
  Subtitle : 31st Annual Conference on Neural Information Processing Systems (NIPS 2017)
Source Genre: Proceedings
 Creator(s):
Guyon, I1, Editor
von Luxburg, U.2, Author           
Bengio, S.1, Editor
Wallach, H.1, Editor
Fergus, R.1, Editor
Vishwanathan, S.1, Editor
Garnett, R.1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
2 Max Planck Fellow Group Statistical Learning Theory, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_3031011            
Publ. Info: Red Hook, NY : Curran Associates, Inc.
Pages: - Volume / Issue: 2 Sequence Number: - Start / End Page: 1236 - 1246 Identifier: URI: https://papers.nips.cc/paper/2017
ISBN: 978-1-5108-6096-4