Distributed Optimization
and Games (DOG)
Giovanni Neglia
Goal
 Make you understand existing distributed algorithms in
communication networks
 Provide you with some hints about how to engineer new
distributed protocols
Goal
 Make you understand how local interactions among
agents in a network have a global effect
Biology
Economy
Info
http://www-sop.inria.fr/members/Giovanni.Neglia/dog15/
(also look at 2014 course to know what’s coming)
[email protected]
Every lesson
 A short test (10-15 minutes) about the previous lesson
 Some specific examples/case studies
 take-home lessons
 Techniques/concepts to study similar problems
Resources (all available online!)
1) Book chapters
 Kelly&Yudovina, Stochastic networks
 Srinivas Shakkottai and R. Srikant, Network Optimization
and Control,
 David Easley and Jon Kleinberg, Networks, Crowds, and
Markets
 J. R. Marden and J.S. Shamma, Game Theory and
Distributed Control
2) Slides
3) Your notes
Evaluation
 in-class closed-book tests, top 4 out of 5 marks will count
for 15% of the final mark
 scribe notes, 2-person teams will make notes available for
lessons 3, 4, 6, 7 (15% final mark)
 1 homework to be delivered before lesson 6 (15% final
mark)
 Final exam (55% final mark)