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What can I do here? A Theory of Affordances in Reinforcement Learning

What can I do here? A Theory of Affordances in Reinforcement Learning

26 June 2020
Khimya Khetarpal
Zafarali Ahmed
Gheorghe Comanici
David Abel
Doina Precup
ArXivPDFHTML

Papers citing "What can I do here? A Theory of Affordances in Reinforcement Learning"

18 / 18 papers shown
Title
Cracking the Code of Action: a Generative Approach to Affordances for Reinforcement Learning
Cracking the Code of Action: a Generative Approach to Affordances for Reinforcement Learning
Lynn Cherif
Flemming Kondrup
David Venuto
Ankit Anand
Doina Precup
Khimya Khetarpal
LM&Ro
54
0
0
24 Apr 2025
Safety through Permissibility: Shield Construction for Fast and Safe
  Reinforcement Learning
Safety through Permissibility: Shield Construction for Fast and Safe Reinforcement Learning
A. Politowicz
Sahisnu Mazumder
Bing-Quan Liu
31
0
0
29 May 2024
CCIL: Continuity-based Data Augmentation for Corrective Imitation
  Learning
CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning
Liyiming Ke
Yunchu Zhang
Abhay Deshpande
S. Srinivasa
Abhishek Gupta
OffRL
27
12
0
19 Oct 2023
Recent Advances of Deep Robotic Affordance Learning: A Reinforcement
  Learning Perspective
Recent Advances of Deep Robotic Affordance Learning: A Reinforcement Learning Perspective
Xintong Yang
Ze Ji
Jing Wu
Yunyu Lai
46
12
0
09 Mar 2023
A Rubric for Human-like Agents and NeuroAI
A Rubric for Human-like Agents and NeuroAI
Ida Momennejad
60
14
0
08 Dec 2022
Discrete Factorial Representations as an Abstraction for Goal
  Conditioned Reinforcement Learning
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning
Riashat Islam
Hongyu Zang
Anirudh Goyal
Alex Lamb
Kenji Kawaguchi
Xin-hui Li
Romain Laroche
Yoshua Bengio
Rémi Tachet des Combes
OffRL
AI4CE
28
9
0
01 Nov 2022
Affordance Extraction with an External Knowledge Database for Text-Based
  Simulated Environments
Affordance Extraction with an External Knowledge Database for Text-Based Simulated Environments
P. Gelhausen
M. Fischer
G. Peters
36
1
0
01 Jul 2022
Goal-Space Planning with Subgoal Models
Goal-Space Planning with Subgoal Models
Chun-Ping Lo
Kevin Roice
Parham Mohammad Panahi
Scott M. Jordan
Adam White
Gábor Mihucz
Farzane Aminmansour
Martha White
29
5
0
06 Jun 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
Bayesian deep learning of affordances from RGB images
Bayesian deep learning of affordances from RGB images
Lorenzo Mur-Labadia
Ruben Martinez-Cantin
UQCV
BDL
16
0
0
27 Sep 2021
Temporally Abstract Partial Models
Temporally Abstract Partial Models
Khimya Khetarpal
Zafarali Ahmed
Gheorghe Comanici
Doina Precup
26
14
0
06 Aug 2021
Iterative Bounding MDPs: Learning Interpretable Policies via
  Non-Interpretable Methods
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods
Nicholay Topin
Stephanie Milani
Fei Fang
Manuela Veloso
OffRL
29
32
0
25 Feb 2021
HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem
  Solving
HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving
Sirui Xie
Xiaojian Ma
Peiyu Yu
Yixin Zhu
Ying Nian Wu
Song-Chun Zhu
42
20
0
22 Feb 2021
Relative Variational Intrinsic Control
Relative Variational Intrinsic Control
Kate Baumli
David Warde-Farley
Steven Hansen
Volodymyr Mnih
26
42
0
14 Dec 2020
Deep Affordance Foresight: Planning Through What Can Be Done in the
  Future
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
33
71
0
17 Nov 2020
Affordance as general value function: A computational model
Affordance as general value function: A computational model
D. Graves
Johannes Günther
Jun Luo
AI4CE
21
6
0
27 Oct 2020
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement
  Learning
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning
Tianren Zhang
Shangqi Guo
Tian Tan
Xiaolin Hu
Feng Chen
30
82
0
20 Jun 2020
FAME: 3D Shape Generation via Functionality-Aware Model Evolution
FAME: 3D Shape Generation via Functionality-Aware Model Evolution
Yanran Guan
Han Liu
Kun Liu
K. Yin
Ruizhen Hu
...
Yan Zhang
Ersin Yumer
N. Carr
R. Měch
Hao Zhang
10
16
0
09 May 2020
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