I did hon­ours in com­puter sci­ence in 2007, under the super­vi­sion of Dr Tasos Viglas at the School of Inform­a­tion Tech­no­lo­gies at the Uni­ver­sity of Sydney.


In a net­work, greedy, inde­pend­ent agents aim to min­im­ise their own per­son­al cost (such as travel time between source and des­tin­a­tion) without regard to wider, soci­et­al impacts of their beha­viour. The inef­fi­ciency due to this beha­viour can be stud­ied through such meas­ures as the price of anarchy, which is the ratio of the cost of the worst-case Nash equi­lib­ri­um to that of the optim­al flow. One applic­a­tion of this game the­or­et­ic ana­lys­is is in allow­ing net­work oper­at­ors to charge users equit­ably and prof­it­ably for mul­tic­ast traffic sent through their net­works, because mul­tic­ast traffic along a link can­not be simply attrib­uted to one par­tic­u­lar user. The aim of the pro­ject is to extend and modi­fy exist­ing mod­els of mul­tic­ast pri­cing, to improve the res­ult­ant soci­et­al cost even with greedy, inde­pend­ent agents and their applic­ab­il­ity to real-world mul­tic­ast uses. The­or­et­ic­al prop­er­ties, such as time and net­work over­head com­plex­ity, will be examined to determ­ine the tract­ab­il­ity of the mod­els.


For INFO4990 (IT Research Methods) course