ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1806.09351
  4. Cited By
Multi-objective Model-based Policy Search for Data-efficient Learning
  with Sparse Rewards

Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards

25 June 2018
Rituraj Kaushik
Konstantinos Chatzilygeroudis
Jean-Baptiste Mouret
ArXivPDFHTML

Papers citing "Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards"

7 / 7 papers shown
Title
Learning Skill-based Industrial Robot Tasks with User Priors
Learning Skill-based Industrial Robot Tasks with User Priors
Matthias Mayr
Carl Hvarfner
Konstantinos Chatzilygeroudis
Luigi Nardi
Volker Krueger
27
21
0
02 Aug 2022
Skill-based Multi-objective Reinforcement Learning of Industrial Robot
  Tasks with Planning and Knowledge Integration
Skill-based Multi-objective Reinforcement Learning of Industrial Robot Tasks with Planning and Knowledge Integration
Matthias Mayr
Faseeh Ahmad
Konstantinos Chatzilygeroudis
Luigi Nardi
Volker Krueger
35
28
0
18 Mar 2022
SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies
  Learned in Simulation
SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies Learned in Simulation
Rituraj Kaushik
Karol Arndt
Ville Kyrki
24
8
0
27 Jan 2022
Imaginary Hindsight Experience Replay: Curious Model-based Learning for
  Sparse Reward Tasks
Imaginary Hindsight Experience Replay: Curious Model-based Learning for Sparse Reward Tasks
Robert McCarthy
Qiang Wang
S. Redmond
OffRL
27
15
0
05 Oct 2021
Meta-Reinforcement Learning for Adaptive Motor Control in Changing Robot
  Dynamics and Environments
Meta-Reinforcement Learning for Adaptive Motor Control in Changing Robot Dynamics and Environments
Timothée Anne
Jack Wilkinson
Zhibin Li
23
1
0
19 Jan 2021
Fast Online Adaptation in Robotics through Meta-Learning Embeddings of
  Simulated Priors
Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated Priors
Rituraj Kaushik
Timothée Anne
Jean-Baptiste Mouret
14
52
0
10 Mar 2020
Emergence of Locomotion Behaviours in Rich Environments
Emergence of Locomotion Behaviours in Rich Environments
N. Heess
TB Dhruva
S. Sriram
Jay Lemmon
J. Merel
...
Tom Erez
Ziyun Wang
S. M. Ali Eslami
Martin Riedmiller
David Silver
134
928
0
07 Jul 2017
1