Distributed Optimization and Games (DOG) Giovanni Neglia.

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Presentation transcript:

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 (also look at 2014 course to know what’s coming)

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)