Multi-Task Reinforcement Learning with Context-based Representations

02/11/2021
by   Shagun Sodhani, et al.
18

The benefit of multi-task learning over single-task learning relies on the ability to use relations across tasks to improve performance on any single task. While sharing representations is an important mechanism to share information across tasks, its success depends on how well the structure underlying the tasks is captured. In some real-world situations, we have access to metadata, or additional information about a task, that may not provide any new insight in the context of a single task setup alone but inform relations across multiple tasks. While this metadata can be useful for improving multi-task learning performance, effectively incorporating it can be an additional challenge. We posit that an efficient approach to knowledge transfer is through the use of multiple context-dependent, composable representations shared across a family of tasks. In this framework, metadata can help to learn interpretable representations and provide the context to inform which representations to compose and how to compose them. We use the proposed approach to obtain state-of-the-art results in Meta-World, a challenging multi-task benchmark consisting of 50 distinct robotic manipulation tasks.

READ FULL TEXT

page 3

page 6

research
02/03/2018

Multi-task Learning for Continuous Control

Reliable and effective multi-task learning is a prerequisite for the dev...
research
10/10/2021

Multi-task Learning with Metadata for Music Mood Classification

Mood recognition is an important problem in music informatics and has ke...
research
03/31/2023

Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness

Representation multi-task learning (MTL) and transfer learning (TL) have...
research
04/05/2019

Learning Task Relatedness in Multi-Task Learning for Images in Context

Multimedia applications often require concurrent solutions to multiple t...
research
04/05/2018

Jointly Detecting and Separating Singing Voice: A Multi-Task Approach

A main challenge in applying deep learning to music processing is the av...
research
07/24/2021

Hand Image Understanding via Deep Multi-Task Learning

Analyzing and understanding hand information from multimedia materials l...
research
11/10/2014

Multi-Task Metric Learning on Network Data

Multi-task learning (MTL) improves prediction performance in different c...

Please sign up or login with your details

Forgot password? Click here to reset