Goal Conditioned Policy

Goal-conditioned policies aim to train agents that can achieve diverse goals specified as inputs, enabling flexible and adaptable behavior in complex environments. Current research focuses on improving the efficiency and generalization of these policies, exploring techniques like multi-objective optimization, safe alternative suggestion mechanisms, and the integration of unsupervised learning and temporal abstraction. This research is significant for advancing robotics and AI, enabling robots to perform complex tasks with minimal human intervention and adapt to unforeseen circumstances, and offering insights into efficient planning and decision-making.

Papers

June 9, 2023

Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models
Siyan Zhao, Aditya Grover
Reinforcement Learning Goal Conditioned Policy Offline Policy Generative Training Software Stack

May 18, 2023

Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning
Wenhao Li, Dan Qiao, Baoxiang Wang, Xiangfeng Wang, Bo Jin, Hongyuan Zha
Multi Agent Reinforcement Learning Sparse Reward Goal Conditioned Policy Task Decomposition

May 17, 2023

Goal-Conditioned Supervised Learning with Sub-Goal Prediction
Tom Jurgenson, Aviv Tamar
Goal Conditioned Reinforcement Learning Goal Conditioned Policy Sub Goal

April 26, 2023

Distance Weighted Supervised Learning for Offline Interaction Data
Joey Hejna, Jensen Gao, Dorsa Sadigh
Reinforcement Learning Imitation Learning Goal Conditioned Policy Goal Conditioned Imitation

April 5, 2023

Goal-Conditioned Imitation Learning using Score-based Diffusion Policies
Moritz Reuss, Maximilian Li, Xiaogang Jia, Rudolf Lioutikov
Goal Conditioned Policy Goal Conditioned Behavior Generation Goal Conditioned Imitation

April 3, 2023

Chain-of-Thought Predictive Control
Zhiwei Jia, Fangchen Liu, Vineet Thumuluri, Linghao Chen, Zhiao Huang, Hao Su
Reinforcement Learning Predictive Control Manipulation Task Goal Conditioned Policy Low Level

March 23, 2023

Planning Goals for Exploration
Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman
Environment Exploration Goal Conditioned Reinforcement Learning Goal Conditioned Policy Goal Directed Goal Discovery

March 20, 2023

Imitating Graph-Based Planning with Goal-Conditioned Policies
Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin
Goal Conditioned Reinforcement Learning Goal Conditioned Policy Graph Based Planning

March 16, 2023

March 2, 2023

UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy
Yinzhen Xu, Weikang Wan, Jialiang Zhang, Haoran Liu, Zikang Shan, Hao Shen, Ruicheng Wang, Haoran Geng, Yijia Weng, Jiayi Chen, Tengyu Liu, Li Yi, He Wang
Large Scale Goal Conditioned Policy Grasp Pose Proposal Generation

January 21, 2023

Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction
Shaofei Cai, Zihao Wang, Xiaojian Ma, Anji Liu, Yitao Liang
Open World Goal Conditioned Policy Goal Conditioned Backbone Fine Tuning Multi Task Agent

January 5, 2023

Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping
Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski, Alessandro Lazaric, Karteek Alahari
Reward Function Reward Shaping Long Horizon Task Goal Conditioned Policy Continuous Control Task Offline Goal Conditioned Reinforcement Learning

December 21, 2022

Decision-making and control with diffractive optical networks
Jumin Qiu, Shuyuan Xiao, Lujun Huang, Andrey Miroshnichenko, Dejian Zhang, Tingting Liu, Tianbao Yu
Deep Reinforcement Learning External Control Decision Making Intelligent Robot Goal Conditioned Policy Diffractive Optical Network

November 9, 2022

Leveraging Sequentiality in Reinforcement Learning from a Single Demonstration
Alexandre Chenu, Olivier Serris, Olivier Sigaud, Nicolas Perrin-Gilbert
Reinforcement Learning Deep Reinforcement Learning Video Demonstration Goal Conditioned Policy Complex Robotic Task

October 12, 2022

Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks
Kuan Fang, Patrick Yin, Ashvin Nair, Homer Walke, Gengchen Yan, Sergey Levine
Strong Generalization Offline Reinforcement Learning Affordance Learning Unseen Task Goal Conditioned Policy Offline Data Visuo Motor Control Novel Task

July 10, 2022

LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action
Dhruv Shah, Blazej Osinski, Brian Ichter, Sergey Levine
Natural Language Human Language Vision Paper Robot Navigation Large Pre Trained Model Action Feature Goal Conditioned Policy Long Horizon Navigation

June 23, 2022

Walk the Random Walk: Learning to Discover and Reach Goals Without Supervision
Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski, Karteek Alahari
Random Walk Goal Conditioned Policy Reachability Based Safety Analysis Visual Goal Motion Memory Goal Conditioned Agent

May 22, 2022

Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest Path
Haoyuan Cai, Tengyu Ma, Simon Du
Autonomous Exploration Goal Conditioned Policy Near Optimal Algorithm Stochastic Shortest Path Reward Aware

May 17, 2022

Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space
Kuan Fang, Patrick Yin, Ashvin Nair, Sergey Levine
Latent Space Offline Reinforcement Learning Long Horizon Task Goal Conditioned Reinforcement Learning Pseudo Goal Goal Conditioned Policy Online Fine Tuning Model Free Policy