Elliot AnshelevichDepartment of Computer Science

Interests:• Design and analysis of algorithms,

especially for large decentralized networks.

• Strategic agents in networks and algorithmic game theory.

• Approximation algorithms.

Networks in Theoretical CS

• A major focus of Theoretical Computer Science is the study of networks

• Networks arise in many contexts, with many different properties

• The Internet• Networks of processors• Distributed Databases • Social networks• Control-Flow Networks• Biological networks• . . .

Networks with Independent Agents

• Internet is not centrally controlled• Transportation Networks• Social Networks• Peer-to-peer Networks• Business relationships

• To understand these, cannot assume centralized control• Algorithmic Game Theory studies such agents

Transportation Networks

Traffic patterns are not centrally controlled

Behavior can be very different from centrally controlled traffic

Braess’ Paradox: sometimes building new roads can increase congestion

Transportation Networks

Traffic patterns are not centrally controlled

“Price of anarchy” = quality lost because of agents being self-interested

What do equilibria look like? How to improve them?

Agents in Network Design

• What if network is built by many self-interested agents?

• Properties of resulting network may be very different from the globally optimum one

• Connection Game (e.g. construction of roads and bus stations)

• Autonomous Systems and Contracts

Agents in Network Design

• What if network is built by many self-interested agents?

• Properties of resulting network may be very different from the globally optimum one

• Connection Game– In general, converges to solution within log of optimal– In multicast (single-source) case, can form a good solution– True even for survivable networks

Agents in Network Design

peer peer

customer provider

• What if network is built by many self-interested agents?

• Properties of resulting network may be very different from the globally optimum one

• Connection Game• Autonomous Systems and Contracts

– Characterize stable systems of contracts– Can get the AS’s to agree on a solution within factor 2 of optimal

Diffusion and Epidemiology

Graph : social network (or computer network) Nodes: people/computers Edges: relationships/links

Diffusive network process: disease, idea, computer virus, forest fire

Diffusion and Epidemiology

Graph : social network (or computer network) Nodes: people/computers Edges: relationships/links

Diffusive network process: disease, idea, computer virus, forest fire

Diffusion and Epidemiology

Graph : social network (or computer network) Nodes: people/computers Edges: relationships/links

Diffusive network process: disease, idea, computer virus, forest fire

Diffusion and Epidemiology

Graph : social network (or computer network) Nodes: people/computers Edges: relationships/links

Diffusive network process: disease, idea, computer virus, forest fire

Immunization

Stop the spread by immunizing/protecting nodes/edges Goal: immunize few, protect many from infection

Immunization

Stop the spread by immunizing/protecting nodes/edges Goal: immunize few, protect many from infection Somewhat know what to do if immunizing in advance What if immunizing in real-time?

Thank you.

If want to learn more, take

Algorithmic Game Theory Spring 09