by @meneguzzi
Presented as the SICSA Distinguished Visiting Fellow master class on October 17th, 2017 at the University of Aberdeen
Plan and goal recognition is the task of inferring the plan and goal of an agent through the observation of its actions and its environment and has a number of applications on computer-human interaction, assistive technologies and surveillance. Although such techniques using planning domain theories have developed a number of very accurate and effective techniques, they often rely on assumptions of full observability and noise-free observations. These assumptions are not necessarily true in the real world, regardless of the technique used to translate sensor data into symbolic logic-based observations. In this tutorial class, we explain plan recognition approaches that rely on a range of assumptions about the available domain knowledge , from complete plan-libraries up to incomplete planning domain theories. We end the tutorial explaining applications of these techniques in two specific areas: multiagent systems and video data recognition.
Here is the latest version of the Slides for the: Master Class on Plan and Goal Recognition
Video of the lecture is available online:
| Time | Activity | Location |
|---|---|---|
| 10h30am | Welcome and Registration | Room 224 |
| 11h | Introduction | Room 224 |
| 11h30 | Goal Recognition with Landmarks - Part 1 | Room 224 |
| 12h30 | Lunch break | - |
| 13h30 | Goal Recognition with Landmarks - Part 2 | Room 224 |
| 14h30 | Break | - |
| 14h45 | Online Goal Recognition | Room 224 |
| 15h15 | Goal Recognition in Incomplete Domains | Room 224 |
| 16h40 | Applications | Room 224 |
- Goal Recognition as reasoning over Heuristics
- Goal and plan recognition dataset:
- Graphplan Implementation in Java:
pdflatex sicsa-planrecognition-presentation.tex && pdflatex sicsa-planrecognition-presentation.tex && pdflatex sicsa-planrecognition-presentation.tex