Program


Session 1
8:45am to 9:00am Opening remarks
9:00am to 9:40am Invited talk by Michael Littman on "Reinforcement Learning from Users: New Algorithms and Frameworks"
9:40am to 9:58am Toward a General, Scaleable Framework for Bayesian Teaching with Applications to Topic Models by Baxter Eaves and Patrick Shafto. [PDF]
9:58am to 10:16am An Empirical Study of Non-Expert Curriculum Design for Machine Learners by Bei Peng, James MacGlashan, Robert Loftin, Michael Littman, David Roberts and Matthew Taylor. [PDF]
10:16am to 10:34am Learning from Stories: Using Natural Communication to Train Believable Agents by Brent Harrison, Siddhartha Banerjee and Mark Riedl. [PDF]
10:34am to 11:00am Coffee Break
Session 2
11:00am to 11:40am Invited talk by Maya Cakmak on "Mental Model Accuracy in Interactive Machine Learning"
11:40am to 11:58am Exploiting Interaction Dynamics for Learning Collaborative Robot Behaviors by Leonel Rozo, Jo√£o Silverio, Sylvain Calinon and Darwin G. Caldwell. [PDF]
11:58am to 12:16pm Policy Shaping from Simulated Critique in Domains with Multiple Optimal Policies by Himanshu Sahni, Brent Harrison, Kaushik Subramanian, Thomas Cederborg, Charles Isbell and Andrea Thomaz. [PDF]
12:16pm to 1:00pm Invited talk by Brenden Lake on "Towards Active Learning with Richer Questions"
1:00pm to 2:15pm Lunch
Session 3
2:15pm to 2:33pm Rapidly Exploring Learning Trees by Kyriacos Shiarlis, Joao Messias and Shimon Whiteson. [PDF]
2:33pm to 2:51pm Active Transfer Learning Using Knowledge of Anticipated Changes by Matthew Williams and Hala Mostafa. [PDF]
2:51pm to 3:31pm Invited talk by Peter Stone on "Interactive ML for Building-Wide Intelligence"
3:31pm to 4:00pm Coffee Break
Session 4
4:00pm to 5:00pm Poster session
5:00pm to 5:45pm Panel discussion on "Realities of Interactive Machine Learning" moderated by Charles Isbell. Panelists: Maya Cakmak, Brenden Lake, Michael Littman, Peter Stone.
5:45pm to 6:00pm Closing remarks