Human-in-the-Loop Planning and Decision Support
Sunday, 01/25/2015, 2:00pm – 6:00pm
Location: Texas 1 Ballroom
Hyatt Regency Austin (Barton Springs)
Endowing an automated agent with the ability to "plan" -- i.e., converting its high-level goals into an executable course of action -- has been a long-standing quest in Artificial Intelligence. For much of the history of automated planning, the dominant research theme has been efficient synthesis of plans under increasingly expressive system dynamics (classical, temporal, stochastic etc.).
An implicit assumption underlying this research has been that the planner's responsibilities start with taking a complete specification, and end with giving out a complete course of action. This assumption is no longer valid when humans are part of the decision making loop, as is the case in an increasing number of decision support and human-machine teaming scenarios.
In this tutorial, we will identify the research challenges in human-in-the-loop planning, including the need to interpret the goals/intentions of the humans in the loop, the need to support continual planning and replanning, the need to unobtrusively support team-decision making, and above all the need to handle pervasive incompleteness in the domain models as well as problem specification. We will then survey current solutions to these problems grounded in the context of human-robot teaming, decision support systems and crowd-sourced planning.
Overview (Tutorial Slides (Final version, as given)[PDF] )
1. Introduction [45min] (Video)
2. Challenge: Interpretation [30min] (Video)
3. Challenge: Decision Support
a. Explicit Constraints [30min] (Video)
b. Implicit Constraints (Preferences) [15+15] (Video for 3b & 3c)
c. Incomplete Dynamics
4. Challenge: Communication
a. Excuses & Explanations
b. Asking for Help
5. Case Study: Human-Robot Teaming & Crowdsourced Planning [30min] (Video)
6. Summary (Video)
Subbarao Kambhampati is a professor of
Computer Science at Arizona State University. He is a
AAAI Fellow and AAAI President-Elect, IJCAI Trustee, AAAI 2005 Co-chair, and
IJCAI 2016 Program Chair. He has presented several well-attended and successful
tutorials in past AAAIs.
Kartik Talamadupula is a research staff
member at IBM T.J. Watson Research Center in Yorktown Heights, NY. His
research focuses on the use of automated planners in integrated
human-in-the-loop AI systems. He is a recipient of the SFAz
Fellowship and a University Graduate Fellowship.