BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201120T120000
DTEND;TZID=America/New_York:20201120T130000
DTSTAMP:20260407T092019
CREATED:20201111T191453Z
LAST-MODIFIED:20201111T191453Z
UID:3681-1605873600-1605877200@seasevents.nmsdev7.com
SUMMARY:SIG Seminar:"Behavior Modeling using Data from Games"
DESCRIPTION:Behavior modeling is an important area of research as it severs many applications and disciplines; it expands on our knowledge of human behavior as well as allows us to develop novel AI entities that adapts to its users or mimics them. This area of research is by definition interdisciplinary and has stimulated interest from multiple funding organizations. In the past few years\, games have emerged as a new platform with large context-rich data that has the utility to advance behavior modeling. In particular\, recently there has been much work investigating the use of MOBA games\, such as League of Legends and Dota\, and Massively Multiplayer games\, such as Eve Online\, for this purpose. Even though there are many exciting new results\, the current techniques and methods for modeling player behaviors within these environments are still in their infancy. In this talk\, I will discuss our current work towards developing a methodological platform to develop player models that leverages and builds on current theory and data-driven techniques\, including machine learning and visualization methods.
URL:https://seasevents.nmsdev7.com/event/sig-seminarbehavior-modeling-using-data-from-games/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
END:VCALENDAR