Great! Thanks for keeping us in the loop, Nadeem! Adam
On Fri, Sep 6, 2013 at 10:09 AM, Nadeem Anjum <[email protected]>wrote: > Hi All, > > Me and Ramyaa exchanged some emails to discuss the algorithm for memory. > > I am available for a Skype meeting anytime now onwards and over the > weekend. On week days, I have my classes, but I am available all evenings > (IST) and some afternoons too. If we plan to meet on a weekday, I will > share my exact hours of availability (as it depends on the day for mornings > and afternoons). > > Thanks, > Nadeem > > > On Fri, Sep 6, 2013 at 7:34 PM, Adam Estrada <[email protected]>wrote: > >> All, >> >> Did Ra myaa get a chance to talk with Nadeem at all last week? >> >> Thanks, >> Adam >> >> >> On Fri, Sep 6, 2013 at 9:19 AM, Arvind Verma <[email protected]>wrote: >> >>> Hi Everyone >>> Can we meet @ Skype and discuss this? >>> Except M W afternoons and evenings I am available at all other times >>> Arvind >>> >>> >>> On Fri, Sep 6, 2013 at 7:34 AM, Nadeem Anjum <[email protected] >>> >wrote: >>> >>> > PS: as of now only cities in taiwan, say taipei are supported (due to >>> the >>> > server database having open street map data of taiwan only). >>> > >>> > >>> > On Friday, September 6, 2013, Nadeem Anjum wrote: >>> > >>> >> Hi All, >>> >> >>> >> I have implemented memory funtion for the simulation. Now the user can >>> >> mark any number of crime spots on the map. Each crime spot is >>> associated >>> >> with reward, risk and no. of times the agent has passed by the >>> vicinity of >>> >> that crime spot. It is represented as <reward, risk, number of times> >>> in >>> >> the label for the spot on the map. >>> >> >>> >> You can have a lok at it here: >>> >> http://gw76.iu.xsede.org/criminfo/index.html >>> >> >>> >> I have saved a sample simulation by the name - memtest. You can click >>> on >>> >> "load" and enter: memtest to load that sample simulation. Or you can >>> run a >>> >> new simulation yourself. >>> >> >>> >> The next step i guess would be determining whether the agent breaks >>> into >>> >> a crime spot. This would be a factor of reward, risk and the number of >>> >> times the spot has been visited. We could assign different weights to >>> the >>> >> above factors. Please let me the model I should use asap. >>> >> >>> >> Thanks, >>> >> Nadeem. >>> >> >>> >> >>> >> -- >>> >> Sent from my iPad >>> >> >>> > >>> > >>> > -- >>> > Sent from my iPad >>> > >>> >> >> >
