Robust Task

Robust task execution focuses on developing systems capable of reliably completing tasks, even under uncertainty or changing conditions. Current research emphasizes methods for efficient multi-task learning, including robust clustering algorithms to handle outlier tasks and hierarchical agent systems for complex problem decomposition. These advancements are crucial for improving the adaptability and reliability of artificial intelligence systems in diverse applications, ranging from robotics and continual learning to large language model deployment. The ultimate goal is to create more robust and efficient AI agents that can handle real-world complexities.

Papers

August 2, 2024

Synergistic pathways of modulation enable robust task packing within neural dynamics
Giacomo Vedovati, ShiNung Ching
Brain Network Neural Dynamic Digital Modulation Synergistic Information Contextual Modulation Neuronal Dynamic Robust Task

April 4, 2024

Multi-task learning via robust regularized clustering with non-convex group penalties
Akira Okazaki, Shuichi Kawano
Multi Task Learning Multi Task Data Clustering Robust Clustering Outlier Detection Task Non Convex Penalty Robust Task

November 28, 2023

Agents meet OKR: An Object and Key Results Driven Agent System with Hierarchical Self-Collaboration and Self-Evaluation
Yi Zheng, Chongyang Ma, Kanle Shi, Haibin Huang
Agent Smith Arbitrary Object Agent System Self Feedback Hierarchical Agent Reflex Prediction Robust Task Bionic Reflex

November 26, 2023

Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning
Jiaqi Li, Yuanhao Lai, Rui Wang, Changjian Shui, Sabyasachi Sahoo, Charles X. Ling, Shichun Yang, Boyu Wang, Christian Gagné, Fan Zhou
Continual LEArning Hessian Matrix Low Rank Approximation Small Perturbation Robust Continual Learning Robust Task

April 29, 2023

Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning
Mingyang Wang, Zhenshan Bing, Xiangtong Yao, Shuai Wang, Hang Su, Chenguang Yang, Kai Huang, Alois Knoll
Self Supervised Meta Reinforcement Learning Task Distribution Meta Reinforcement Robust Task

May 22, 2022

A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning
Zhi Wang, Chunlin Chen, Daoyi Dong
Reinforcement Learning Lifelong Reinforcement Learning Task Distribution Dirichlet Process Robust Task

April 17, 2022

Robust Task Planning for Assembly Lines with Human-Robot Collaboration
Jessica Leu, Yujiao Cheng, Changliu Liu, Masayoshi Tomizuka
Task Planning Human Robot Collaboration Robust Planning Assembly Line Robust Task Completion Time

Robust Task

Papers

Synergistic pathways of modulation enable robust task packing within neural dynamics

Multi-task learning via robust regularized clustering with non-convex group penalties

Agents meet OKR: An Object and Key Results Driven Agent System with Hierarchical Self-Collaboration and Self-Evaluation

Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning

Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning

A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning

Robust Task Planning for Assembly Lines with Human-Robot Collaboration