Offline Goal-Conditioned Reinforcement Learning (Offline GCRL) is an important problem in RL that focuses on acquiring diverse goal-oriented skills solely from pre-collected behavior datasets. 
In this setting, the reward feedback is typically absent except when the goal is achieved, 
which makes it difficult to learn policies especially from a finite dataset of suboptimal behaviors.
In addition, realistic scenarios involve long-horizon planning, which necessitates the 
extraction of useful skills within sub-trajectories.
Recently, the conditional diffusion model has been shown to be a promising approach to 
generate high-quality long-horizon plans for RL. 
However, their
practicality for the goal-conditioned setting is still limited due to a number of technical assumptions
made by the methods.
In this paper, we propose \textit{SSD (Sub-trajectory Stitching with Diffusion)}, 
a model-based offline GCRL method that leverages the conditional diffusion model to address these limitations. 
In summary, we use the diffusion model that generates future plans conditioned on the target goal and value, 
with the target value estimated from the goal-relabeled offline dataset. % to address the issue of long-horizon planning. 
We report state-of-the-art performance in the standard benchmark set of GCRL tasks, and 
demonstrate the capability to successfully stitch the segments of suboptimal trajectories in the offline data to generate high-quality plans.

Stitching Sub-trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL | VIDEO

Main Track - Machine Learning

technical paper

We are pleased to announce the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), which will be held in Vancouver, British Columbia at the Vancouver Convention Centre – West Building from 20-27 February, 2024.

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-24 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and a range of other activities to be announced.

We expect for AAAI-24 to be an in-person conference – one author of all accepted papers will be expected to present work in person unless there are exceptional circumstances that prevent this.<br><br><br><br>

In order to access the AAAI-24 event page you need to register [here](https://aaai.org/aaai-conference/registration/)

AAAI 2024

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. 

Sungyoon Kim

1

11

1

SHORT BIO

Presentations

Stitching Sub-trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL | VIDEO

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES