Multi-Goal Reinforcement Learning

17 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

Learning Discrete State Abstractions With Deep Variational Inference

ondrejba/discrete_abstractions pproximateinference AABI Symposium 2021

In this work, we propose an information bottleneck method for learning approximate bisimulations, a type of state abstraction.

Counterfactual Data Augmentation using Locally Factored Dynamics

spitis/mrl NeurIPS 2020

Many dynamic processes, including common scenarios in robotic control and reinforcement learning (RL), involve a set of interacting subprocesses.

ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning

yufeiwang63/ROLL 13 Nov 2020

Current image-based reinforcement learning (RL) algorithms typically operate on the whole image without performing object-level reasoning.

Adversarial Intrinsic Motivation for Reinforcement Learning

iDurugkar/adversarial-intrinsic-motivation NeurIPS 2021

In this paper, we investigate whether one such objective, the Wasserstein-1 distance between a policy's state visitation distribution and a target distribution, can be utilized effectively for reinforcement learning (RL) tasks.

Multi-Goal Reinforcement Learning environments for simulated Franka Emika Panda robot

qgallouedec/panda-gym 25 Jun 2021

This technical report presents panda-gym, a set Reinforcement Learning (RL) environments for the Franka Emika Panda robot integrated with OpenAI Gym.

Bilinear value networks

improbable-ai/bvn 28 Apr 2022

The dominant framework for off-policy multi-goal reinforcement learning involves estimating goal conditioned Q-value function.

RoMo-HER: Robust Model-based Hindsight Experience Replay

kaixindelele/RHER 28 Jun 2023

In our paper, we design a robust framework called Robust Model-based Hindsight Experience Replay (RoMo-HER) which can effectively utilize the dynamical model in robot manipulation environments to enhance the sample efficiency.