3 papers
cs.AI2026
Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions
Rashmeet Kaur Nayyar, Naman Shah, Siddharth Srivastava
Real-world sequential decision-making often involves parameterized action spaces that require both, decisions regarding discrete actions and decisions about continuous action param…
cs.RO2025
From Real World to Logic and Back: Learning Generalizable Relational Concepts For Long Horizon Robot Planning
Naman Shah, Jayesh Nagpal, Siddharth Srivastava
Robots still lag behind humans in their ability to generalize from limited experience, particularly when transferring learned behaviors to long-horizon tasks in unseen environments…
cs.RO2025
Using Explainable AI and Hierarchical Planning for Outreach with Robots
Rushang Karia, Jayesh Nagpal, Daksh Dobhal +4
Understanding how robots plan and execute tasks is crucial in today's world, where they are becoming more prevalent in our daily lives. However, teaching non-experts, such as K-12…