Multi-Goal Reinforcement Learning
17 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Multi-Goal Reinforcement Learning
Most implemented papers
Learning Discrete State Abstractions With Deep Variational Inference
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
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
Current image-based reinforcement learning (RL) algorithms typically operate on the whole image without performing object-level reasoning.
Adversarial Intrinsic Motivation for Reinforcement Learning
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
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
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
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.