This post discusses our work “Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks,” published at AAAI 2021.

This post discusses our work “CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs,” published at CoRL 2020.

In our recent work, we consider strategies for effective and efficient decision-making that lie between the two extremes of pure learning and pure planning. Our main idea is to learn to generate abstractions of problems that afford faster planning.

Natural science and engineering science Cognitive science and neuroscience study the processes by which humans and other animals generate behavior that is intelligent: robust, flexible, and effective at achieving and maintaining the welfare of the individual. Artificial intelligence studies the processes by which computers can generate behavior that is intelligent: robust, flexible, and effective at […]