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What Can I Do Here? Learning New Skills by Imagining Visual Affordances

What Can I Do Here? Learning New Skills by Imagining Visual Affordances

1 June 2021
Alexander Khazatsky
Ashvin Nair
Dan Jing
Sergey Levine
    LM&Ro
ArXivPDFHTML

Papers citing "What Can I Do Here? Learning New Skills by Imagining Visual Affordances"

16 / 16 papers shown
Title
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
Caleb Chuck
Fan Feng
Carl Qi
Chang Shi
Siddhant Agarwal
Amy Zhang
S. Niekum
47
0
0
06 May 2025
Goal-Conditioned Reinforcement Learning with Disentanglement-based
  Reachability Planning
Goal-Conditioned Reinforcement Learning with Disentanglement-based Reachability Planning
Zhifeng Qian
Mingyu You
Hongjun Zhou
Xuanhui Xu
Bin He
26
3
0
20 Jul 2023
Visual Affordance Prediction for Guiding Robot Exploration
Visual Affordance Prediction for Guiding Robot Exploration
Homanga Bharadhwaj
Abhi Gupta
Shubham Tulsiani
44
12
0
28 May 2023
Learning Sim-to-Real Dense Object Descriptors for Robotic Manipulation
Learning Sim-to-Real Dense Object Descriptors for Robotic Manipulation
Hoang-Giang Cao
Weihao Zeng
I-Chen Wu
35
3
0
18 Apr 2023
Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for
  Industrial Insertion of Novel Connectors from Vision
Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for Industrial Insertion of Novel Connectors from Vision
Ashvin Nair
Brian Zhu
Gokul Narayanan
Eugen Solowjow
Sergey Levine
OffRL
OnRL
28
15
0
27 Oct 2022
An information-theoretic perspective on intrinsic motivation in
  reinforcement learning: a survey
An information-theoretic perspective on intrinsic motivation in reinforcement learning: a survey
A. Aubret
L. Matignon
S. Hassas
37
35
0
19 Sep 2022
Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in
  Latent Space
Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space
Kuan Fang
Patrick Yin
Ashvin Nair
Sergey Levine
OffRL
58
29
0
17 May 2022
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning
Philippe Hansen-Estruch
Amy Zhang
Ashvin Nair
Patrick Yin
Sergey Levine
AI4CE
35
28
0
27 Apr 2022
Possibility Before Utility: Learning And Using Hierarchical Affordances
Possibility Before Utility: Learning And Using Hierarchical Affordances
Robby Costales
Shariq Iqbal
Fei Sha
29
5
0
23 Mar 2022
PLATO: Predicting Latent Affordances Through Object-Centric Play
PLATO: Predicting Latent Affordances Through Object-Centric Play
Suneel Belkhale
Dorsa Sadigh
OffRL
30
13
0
10 Mar 2022
Weakly Supervised Disentangled Representation for Goal-conditioned
  Reinforcement Learning
Weakly Supervised Disentangled Representation for Goal-conditioned Reinforcement Learning
Zhifeng Qian
Mingyu You
Hongjun Zhou
Bin He
DRL
OffRL
41
7
0
28 Feb 2022
Goal-Conditioned Reinforcement Learning: Problems and Solutions
Goal-Conditioned Reinforcement Learning: Problems and Solutions
Minghuan Liu
Menghui Zhu
Weinan Zhang
35
133
0
20 Jan 2022
A Workflow for Offline Model-Free Robotic Reinforcement Learning
A Workflow for Offline Model-Free Robotic Reinforcement Learning
Aviral Kumar
Anika Singh
Stephen Tian
Chelsea Finn
Sergey Levine
OffRL
143
85
0
22 Sep 2021
Offline Meta-Reinforcement Learning with Online Self-Supervision
Offline Meta-Reinforcement Learning with Online Self-Supervision
Vitchyr H. Pong
Ashvin Nair
Laura M. Smith
Catherine Huang
Sergey Levine
OffRL
32
66
0
08 Jul 2021
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy
  Learning
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning
Yuexiang Zhai
Christina Baek
Zhengyuan Zhou
Jiantao Jiao
Yi Ma
27
22
0
08 Jul 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
457
11,715
0
09 Mar 2017
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