Stanford Intelligent and Interactive Autonomous Systems Group (ILIAD) develops algorithms for AI agents that safely and reliably interact with people. Our mission is to develop theoretical foundations for human-robot and human-AI interaction. Our group is focused on: 1) formalizing interaction and developing new learning and control algorithms for interactive systems inspired by tools and techniques from game theory, cognitive science, optimization, and representation learning, and 2) developing practical robotics algorithms that enable robots to safely and seamlessly coordinate, collaborate, compete, or influence humans.
Recent NewsCheck out our YouTube channel for latest talks and supplementary videos for our publications.
|Jul 9, 2021:||Our paper titled "Learning How to Dynamically Route Autonomous Vehicles on Shared Roads" got accepted to Transportation Research Part C: Emerging Technologies!|
|Jul 6, 2021:||Our paper titled "Learning Latent Actions to Control Assistive Robots" got accepted to the Journal of Autonomous Robots (AURO)!|
|Jun 30, 2021:||Our paper titled "Cooperative Autonomous Vehicles that Sympathize with Human Drivers" got accepted to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)!|
|Jun 15, 2021:||Our paper titled "Targeted Data Acquisition for Evolving Negotiation Agents" got accepted to the 38th International Conference on Machine Learning (ICML)!|
|May 18, 2021:||Our paper titled "Emergent Prosociality in Multi-Agent Games Through Gifting" got accepted to the 30th International Joint Conference on Artificial Intelligence (IJCAI)!|