The Paradox of Choice: Using Attention in Hierarchical Reinforcement Learning

24 January 2022

Papers citing "The Paradox of Choice: Using Attention in Hierarchical Reinforcement Learning"

11 / 11 papers shown

Title
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances Michael Ahn Anthony Brohan Noah Brown Yevgen Chebotar Omar Cortes ... Ted Xiao Peng Xu Sichun Xu Mengyuan Yan Andy Zeng LM&Ro 159 1,940 0 04 Apr 2022
Deep Affordance Foresight: Planning Through What Can Be Done in the Future Danfei Xu Ajay Mandlekar Roberto Martín-Martín Yuke Zhu Silvio Savarese Li Fei-Fei 52 71 0 17 Nov 2020
Options of Interest: Temporal Abstraction with Interest Functions Khimya Khetarpal Martin Klissarov Maxime Chevalier-Boisvert Pierre-Luc Bacon Doina Precup 39 45 0 01 Jan 2020
The Termination Critic Anna Harutyunyan Will Dabney Diana Borsa N. Heess Rémi Munos Doina Precup OffRL 40 48 0 26 Feb 2019
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation Tejas D. Kulkarni Karthik Narasimhan A. Saeedi J. Tenenbaum 68 1,134 0 20 Apr 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 348 7,956 0 17 Aug 2015
An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning R. Sutton A. R. Mahmood Martha White 82 269 0 14 Mar 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention Ke Xu Jimmy Ba Ryan Kiros Kyunghyun Cho Aaron Courville Ruslan Salakhutdinov R. Zemel Yoshua Bengio DiffM 308 10,050 0 10 Feb 2015
Salient Object Detection: A Benchmark Ali Borji Ming-Ming Cheng Huaizu Jiang Jia Li 98 1,726 0 05 Jan 2015
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 499 27,263 0 01 Sep 2014
Empowerment -- an Introduction Christoph Salge C. Glackin Daniel Polani 73 181 0 07 Oct 2013