Skip to content

Rashmeet09/AAIR-lab

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

38 Commits
 
 
 
 
 
 

Repository files navigation

AAIR Lab LogoAAIR Lab Logo

Public Code Repository
   AAIR Lab, ASU



2025

  • From the Real World to Logic and Back: Learning Symbolic World Models for Long Horizon Planning.
    Naman Shah, Jayesh Nagpal, Siddharth Srivastava.
    In Proceedings of CoRL 2025. (to appear)

  

  • Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks.
    Rushang Karia*, Daniel Bramblett*, Daksh Dobhal, Siddharth Srivastava.
    In Proceedings of ICLR 2025.

  

  • Autonomous Option Invention for Continual Hierarchical Reinforcement Learning and Planning.
    Rashmeet Kaur Nayyar, Siddharth Srivastava.
    In Proceedings of AAAI, 2025.

  

  • Using Explainable AI and Hierarchical Planning for Outreach with Robots.
    Rushang Karia*, Jayesh Nagpal*, Daksh Dobhal*, Pulkit Verma, Rashmeet Kaur Nayyar, Naman Shah, Siddharth Srivastava.
    In Proceedings of EAAI, 2025.

  

2024

  • Belief-State Query Policies for User-Aligned POMDPs.
    Daniel Bramblett, Siddharth Srivastava.
    In Proceedings of NeurIPS, 2024.

  

  • Epistemic Exploration for Generalizable Planning and Learning in Non-Stationary Settings.
    Rushang Karia*, Pulkit Verma*, Alberto Speranzon, Siddharth Srivastava.
    In Proceedings of ICAPS, 2024.

  

2023

  • Autonomous Capability Assessment of Sequential Decision-Making Systems in Stochastic Settings.
    Pulkit Verma, Rushang Karia, Siddharth Srivastava.
    In Proceedings of NeurIPS, 2023.

  

  • Conditional Abstraction Trees for Sample-Efficient Reinforcement Learning.
    Mehdi Dadvar, Rashmeet Kaur Nayyar, Siddharth Srivastava.
    In Proceedings of UAI, 2023.

  

2022

  • Relational Abstractions for Generalized Reinforcement Learning on Symbolic Problems.
    Rushang Karia, Siddharth Srivastava
    In Proceedings of IJCAI, 2022.

  

  • Discovering User-Interpretable Capabilities of Black-Box Planning Agents.
    Pulkit Verma, Shashank Rao Marpally, Siddharth Srivastava.
    In Proceedings of KR, 2022.

  

  • Using Deep Learning to Boostrap Abstractions for Hierarchical Robot Planning.
    Naman Shah, Siddharth Srivastava.
    In Proceedings of AAMAS, 2022.

  

  • JEDAI: A System for Skill-Aligned Explainable Robot Planning (Demonstration Track).
    Naman Shah*, Pulkit Verma*, Trevor Angle, Siddharth Srivastava.
    In Proceedings of AAMAS, 2022.

  

  • Differential Assessment of Black-Box AI Agents.
    Rashmeet Kaur Nayyar*, Pulkit Verma*, Siddharth Srivastava.
    In Proceedings of AAAI, 2022.

  

2021

  • Learning Generalized Relational Heuristic Networks for Model-Agnostic Planning.
    Rushang Karia, Siddharth Srivastava.
    In Proceedings of AAAI, 2021.

  

  • Asking the Right Questions: Learning Interpretable Action Models Through Query Answering.
    Pulkit Verma, Shashank Rao Marpally, Siddharth Srivastava.
    In Proceedings of AAAI, 2021.

  

2020

  • Anytime Task and Motion Policies for Stochastic Environments.
    Naman Shah, Deepak Kala Vasudevan, Kislay Kumar, Pranav Kamojhalla, Siddharth Srivastava.
    In Proceedings of ICRA, 2020.

  

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published