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Interesting Object, Curious Agent: Learning Task-Agnostic Exploration

Interesting Object, Curious Agent: Learning Task-Agnostic Exploration

25 November 2021
Simone Parisi
Victoria Dean
Deepak Pathak
Abhinav Gupta
    LM&Ro
ArXivPDFHTML

Papers citing "Interesting Object, Curious Agent: Learning Task-Agnostic Exploration"

10 / 10 papers shown
Title
World Model Agents with Change-Based Intrinsic Motivation
World Model Agents with Change-Based Intrinsic Motivation
Jeremias Ferrao
Rafael Cunha
OffRL
MoE
52
0
0
26 Mar 2025
Synthesizing Evolving Symbolic Representations for Autonomous Systems
Synthesizing Evolving Symbolic Representations for Autonomous Systems
Gabriele Sartor
A. Oddi
R. Rasconi
V. Santucci
Rosa Meo
21
0
0
18 Sep 2024
Affordances from Human Videos as a Versatile Representation for Robotics
Affordances from Human Videos as a Versatile Representation for Robotics
Shikhar Bahl
Russell Mendonca
Lili Chen
Unnat Jain
Deepak Pathak
37
161
0
17 Apr 2023
Self-Motivated Multi-Agent Exploration
Self-Motivated Multi-Agent Exploration
Shaowei Zhang
Jiahan Cao
Lei Yuan
Yang Yu
De-Chuan Zhan
41
5
0
05 Jan 2023
Choreographer: Learning and Adapting Skills in Imagination
Choreographer: Learning and Adapting Skills in Imagination
Pietro Mazzaglia
Tim Verbelen
Bart Dhoedt
Alexandre Lacoste
Sai Rajeswar
29
21
0
23 Nov 2022
Task-Agnostic Learning to Accomplish New Tasks
Task-Agnostic Learning to Accomplish New Tasks
Xianqi Zhang
Xingtao Wang
Xu Liu
Wenrui Wang
Xiaopeng Fan
Debin Zhao
OffRL
85
0
0
09 Sep 2022
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot
  Object Navigation
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation
S. Gadre
Mitchell Wortsman
Gabriel Ilharco
Ludwig Schmidt
Shuran Song
CLIP
LM&Ro
29
142
0
20 Mar 2022
The Unsurprising Effectiveness of Pre-Trained Vision Models for Control
The Unsurprising Effectiveness of Pre-Trained Vision Models for Control
Simone Parisi
Aravind Rajeswaran
Senthil Purushwalkam
Abhinav Gupta
LM&Ro
28
186
0
07 Mar 2022
Curriculum Learning for Reinforcement Learning Domains: A Framework and
  Survey
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
Sanmit Narvekar
Bei Peng
Matteo Leonetti
Jivko Sinapov
Matthew E. Taylor
Peter Stone
ODL
146
457
0
10 Mar 2020
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
323
11,681
0
09 Mar 2017
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