Nick Hawes

Robot plans execution for information gathering tasks with resources constraints

2015

Partially observable Markov decision processes (POMDPs) have been widely used to model real world problems because of their abilities to capture uncertainty in states, actions and observations. In robotics, there are also constraints imposed on …

Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning

2025 · arXiv (Cornell University)

Neural algorithmic reasoning (NAR) is a paradigm that trains neural networks to execute classic algorithms by supervised learning. Despite its successes, important limitations remain: inability to construct valid solutions without post-processing and to reason about …