22-24 March 2010, AAAI Spring Symposium on Time and Interactive Behaviour, Stanford CA, U.S.A.

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?

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.

For more information, see http://asimov.usc.edu/~mower/aaai10ss_time/