To be held at ICAPS 2023, in Prague, Czech Republic.
This tutorial covers some of the landmark methods in the area of planning action model acquisition that the planning community has produced over the years. From OBSERVER in the early 90’s to the modern forms of action-label-only LOCM techniques, we cover both the concepts behind these approaches and grounded hands-on examples for attendees to try for themselves.
- tutorial_site.md: The source for the tutorial website, hosted on the ICAPS'23 page.
- Dockerfile: The Dockerfile for the tutorial -- can also be pulled directly from dockerhub (see the slides).
- examples.py: The model acquisition examples embedded within the docker image.
- slides: The slides for the tutorial.
Christian is an Assistant Professor at Queen’s University in Kingston, Canada. He completed my PhD under the supervision of Professors Sheila McIlraith and J. Christopher Beck in the area of Automated Planning, with the Knowledge Representation and Reasoning Group at the University of Toronto. Following his PhD, Christian was a post-doc for two years with the University of Melbourne’s Agentlab studying techniques for multi-agent planning with a project on human-agent collaboration, and then subsequently a Research Fellow with the MERS group at MIT’s CSAIL. Just prior to joining Queen’s Christian was a Research Staff Member for two years at the MIT-IBM Watson AI Lab.
Tathagata is a Research Staff Member at IBM Research AI in the AI Composition Lab, Cambridge (MA). His research interests include human-AI interaction, especially planning and collaborative decision-making with humans in the loop, with applications in human-agent teaming and decision support.