So, Where’s My Robot?

Thoughts on Social Machine Learning

Social ML at AAAI

AAAIThis week the American Association of Artificial Intelligence (AAAI) had their annual conference in Boston. There was much to see and lots of reflection on the first 50 years of the field of AI. More than last year’s conference in Pittsburgh, this year I found several papers and talks relevant for those of us interested in Social Machine Learning. Here’s the social learning reading list of AAAI-06:

Humans teaching software game agents:

“Real-Time Evolution of Neural Networks in the NERO Video Game”, Ken Stanley, Bobby Bryant, Igor Karpov, Risto Miikkulanen

“A Simple and Effective Method for Incorporating Advice into Kernel Methods”, Rich Maclin, Jude Shavlik, Trevor Walker, Lisa Torrey

“Reinforcement Learning with Human Teachers”, Andrea Thomaz, Cynthia Breazeal

Personal desktop assistants that learn preferences of a user both implicitly and explicitly. There were several papers on the CALO personal assistant project, here’s a couple I found most interesting:

“Extracting Knowledge about Users’ Activities from Raw Workstation Contents”, Tom Mitchell, Sophie Wang, Yifen Huang, Adam Cheyer

Karen Myers gave an overview keynote, “Developing an Intelligent Personal Assistant”, in which she pointed to some learning aspects of the project (Tailor, LAPDOG, PLOW)

There were several sessions on robotics, and even a whole session on Human-Robot Interaction. Which is great compared to the robotics and HRI representation last year. We had a paper on HRI and robot learning:

“Perspective Taking: An Organizing Principle for Learning in Human-Robot Interaction”, Matt Berlin, Jesse Gray, Andrea Thomaz, Cynthia Breazeal

One of the themes on Thursday was Intelligent Tutoring Systems. Which is the reverse problem of Social Machine Learning, but relevant as it deals with a learning interaction between a human and a machine.

“Cognitive Tutors and Opportunities for Convergence of Human and Machine Learning Theory”, Ken Koedinger’s keynote talk

“Classifying Learner Engagement through Integration of Multiple Data Sources”, Carole Beal, Lei Qu, Hyokyeong Lee

These don’t deal with learning, but are a couple of interesting papers on creating believable behavior in software agents that are meant to interact with people.

“Virtual Humans”, Bill Swartout (AI Magazine article)

“Using Anticipation to Create Believable Behavior”, Carlos Martinho and Ana Paiva

July 21st, 2006 Posted by | Conferences, HCI, Machine Learning | no comments