t's All in the Timing: Representing and Reasoning about Time in Interactive Behavior

Deadline: October 2, 2009

AAAI Spring Symposium Series 2010
March 22-24, 2010, Stanford University, CA, USA

http://asimov.usc.edu/~mower/aaai10ss_time/

People do not experience the world solely as an ordered sequence of events. The timing of our perceptions and behaviors has as much of an impact on our experiences as the nature of the events themselves. Yet many of the representations currently used to model human behavior do not incorporate explicit models of the temporal expression of these stimuli or actions. Dynamic behavior is often modeled sequentially in such a way that its temporal resolution is reduced and potential nonstationarity is ignored for the sake of computational efficiency (as in Markov state-based models of behavior), and/or causal mappings between observations and behavior are simplified to mitigate the sparseness of available datasets. Given that any artificial agent designed to interact with people will be dealing with intelligent partners with rich mental representations of time, are we using the appropriate representations?

The issue of timing can be even more critical when designing natural interactive social behaviors for robots or other synthetic characters. Human social behaviors are extremely dependent on a close feedback loop of simultaneous and coordinated activity between multiple interactors. Yet how to best represent these interdependencies and temporal relationships in order to produce interactive behaviors is just beginning to be explored and understood from a computational perspective. Speed, acceleration, tempo, and delay are concepts that AI and robotics researchers recognize as important in everything from motor control to verbal communication, but we do not yet possess a well-motivated framework for how these temporal considerations should be designed into our systems.

This symposium is oriented towards several different groups of researchers, including, but not limited to: computer scientists who use machine learning techniques to model human behavior, psychologists and neuroscientists who study social behavior, and designers of robots or computational artifacts that interact naturally with humans in real time. By bringing together members of these communities through a shared interest in temporal representations, our goal is to identify critical areas of study and promising techniques. Papers on any aspect of modeling or studying the temporal aspects of human or human-machine social interaction are welcome.


Submissions:

Interested participants may submit either full length papers (up to 6 pages in AAAI format) or short papers/extended abstracts (2 pages). Reports on experimental results, descriptions of implemented systems, and position papers are all welcome. Please e-mail submissions to aaai10sstime@google-mail.com.


Organizing Committee:

Frank Broz (University of Hertfordshire), Marek Michalowski (Carnegie Mellon University), Emily Mower (University of Southern California)