BEGIN:VCALENDAR VERSION:2.0 PRODID:ILLC Website X-WR-TIMEZONE:Europe/Amsterdam BEGIN:VTIMEZONE TZID:Europe/Amsterdam X-LIC-LOCATION:Europe/Amsterdam BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:19700329T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:19701025T030000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:/NewsandEvents/Archives/2010/newsitem/3011/22- 24-March-2010-AAAI-Spring-Symposium-on-Time-and-In teractive-Behaviour-Stanford-CA-U-S-A- DTSTAMP:20090924T000000 SUMMARY:AAAI Spring Symposium on Time and Interact ive Behaviour, Stanford CA, U.S.A. DTSTART;VALUE=DATE:20100322 DTEND;VALUE=DATE:20100324 LOCATION:Stanford CA, U.S.A. DESCRIPTION:People do not experience the world sol ely as an ordered sequence of events. The timing o f our perceptions and behaviors has as much of an impact on our experiences as the nature of the eve nts themselves. Yet many of the representations cu rrently used to model human behavior do not incorp orate explicit models of the temporal expression o f these stimuli or actions. Dynamic behavior is of ten modeled sequentially in such a way that its te mporal resolution is reduced and potential nonstat ionarity is ignored for the sake of computational efficiency (as in Markov state-based models of beh avior), and/or causal mappings between observation s and behavior are simplified to mitigate the spar seness of available datasets. Given that any artif icial agent designed to interact with people will be dealing with intelligent partners with rich men tal representations of time, are we using the appr opriate representations? This symposium is orien ted towards several different groups of researcher s, including, but not limited to: computer scienti sts who use machine learning techniques to model h uman behavior, psychologists and neuroscientists w ho study social behavior, and designers of robots or computational artifacts that interact naturally with humans in real time. By bringing together me mbers of these communities through a shared intere st in temporal representations, our goal is to ide ntify critical areas of study and promising techni ques. For more information, see http://asimov.us c.edu/~mower/aaai10ss_time/ Papers on any aspect of modeling or studying the temporal aspects of h uman or human-machine social interaction are welco me, including reports on experimental results, des criptions of implemented systems, and position pap ers. Submission deadline is October 2, 2009 X-ALT-DESC;FMTTYPE=text/html:
Peopl e do not experience the world solely as an ordered \n sequence of events. The timing of our perc eptions and behaviors\n has as much of an imp act on our experiences as the nature of the\n events themselves. Yet many of the representation s currently\n used to model human behavior do not incorporate explicit models\n of the tem poral expression of these stimuli or actions. Dyna mic\n behavior is often modeled sequentially in such a way that its\n temporal resolution is reduced and potential nonstationarity is\n ignored for the sake of computational efficiency (as in Markov\n state-based models of behavio r), and/or causal mappings between\n observat ions and behavior are simplified to mitigate the\n sparseness of available datasets. Given that any artificial\n agent designed to interact with people will be dealing with\n intelligen t partners with rich mental representations of tim e,\n are we using the appropriate representat ions?\n
\nThis symposium is orie nted towards several different groups\n of re searchers, including, but not limited to: computer \n scientists who use machine learning techni ques to model human\n behavior, psychologists and neuroscientists who study social\n behav ior, and designers of robots or computational arti facts\n that interact naturally with humans i n real time. By bringing\n together members o f these communities through a shared interest\n in temporal representations, our goal is to ide ntify critical\n areas of study and promising techniques.\n
\n \n \nF or more information, see\n http://asimov.usc.edu/~mower/aaai10ss_time/\n
\n Paper s on any aspect of modeling or studying the tempor al\n aspects of human or human-machine soci al interaction are\n welcome, including rep orts on experimental results,\n description s of implemented systems, and position papers.\n Submission deadline is October 2, 2009\n
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