Flexible AI Planning for Proactive Agents in Scenarios with Multiple Possible Goals

This project introduces a new class of multi-goal planning problems that generalizes existing formulations and provides the flexibility to reason over multiple possible goals. We will also develop an open-source tool to solve such problems efficiently, bridging theory and practice and enabling impact across both research and industry applications.

This project is financed by the JPMorganChase Faculty Research Awards.

Deborah Conforto has joined the project as Postdoc.

ConAn: Contrastive Analysis for State-Space Exploration

This project introduces a new concept to guide search in AI Planning: Contrastive Analysis. The key idea is to give AI tools the ability to understand what the advantages and disadvantages of each alternative are. My hypothesis is that this ability is a fundamental skill for decision making and could change the way current AI systems make decisions.

This project is funded by the prestigious Sapere Aude grant, funded by the "Danmarks Frie Forskningsfond" (DFF). Rasmus G. Tollund and Maria Fernanda Salerno are hired as PhD Students thanks to this project.

CheckRead more about that project here.