News and Notes 2/26 Homework 2 due now Midterm March 4 (one week from today) –will cover up to and including “The Web as Network” –closed book: absolutely no auxiliary materials allowed –no notes, books, articles, calculators, laptops, spatulas, etc. Part or all of Tuesday’s class will be a midterm review

Context, Motivation and Influence: the Emergence of the Global from the Local Networked Life CSE 112 Spring 2004 Prof. Michael Kearns

So Far We Have… Examined a wide variety of network types and specifics… –types: content, technological, social, physical, etc. –specifics: the web, Kevin Bacon graph, nervous system, etc. …but a rather limited variety of processes on networks –navigation: forwarding letters or messages –search: finding relevant pages on the web –have primarily examined relatively passive activities In reality, many kinds of activities in (human) networks are: –based on preferences, desires and goals –involve direct or indirect interaction with others –entail interdependent behaviors Broadly speaking, we are entering the domains of –social science –psychology –economics and game theory

Examples from Schelling and Beyond Going to the beach or not –too few  you’ll go, making it more crowded –too many  you won’t go, or will leave if you’re there Sending Christmas cards –people send to those they expect will send to them –everybody hates it, but no individual can break the cycle Investing in an apartment fire sprinkler –only worth it if enough people do it –insurance companies won’t discount for it Choosing where to sit in the Levine Auditorium

Sitting in Levine Would anyone like to change their seat now? Common desires: –having a “buffer zone” –being near an exit or aisle –not wanting to sit in front of someone –not wanting to have to climb over people –not wanting to be climbed over –preferring the front, back, or middle rows 25 liked their seats, 5 indifferent, 1 disliked –may the rest of your lives be so enjoyable… –25 sat in the same place every class, 5 move around –suppose the auditorium were half the size Global desires: ~18 described a different arrangement –move everyone forward –evenly distributed

Choice Quotes “I want to put my feet on the chair in front of me, but I don’t want feet near my head.” “I would try to fulfill the preferences of as many people as possible, instead of completely satisfying only a few.” “All the smart, cute boys would sit near me, and all the other girls can go to the very back.” “My seat would lie where there is the most space between me and the other people.” “I would want to sit in the last third of the auditorium but would also want some people sitting behind me.” “I would be in the third or fourth row with nobody in my row who had to get up and leave. About 10 people would fill the two rows in front of me, and everyone else would be either on the right side (so they don’t walk over me if they leave) or behind me in the back 2/3 of the room.” “I am assuming everyone is happy with their seat because the auditorium is empty enough.”

Global Conflict from Local Preferences You can’t all sit in the back or front rows You can’t all have too large a buffer zone If you like sitting on the aisle, but don’t like being climbed over, you’ll probably be unhappy sooner or later –e.g. by people who like sitting in the middle You can’t have too many who are far from the crowd You can’t all be in the back 1/3 with some behind you Etc. etc. etc. Everyone may have personal preferences that –are rather mild –can easily all be fulfilled with a small (or large) enough group –but are collectively impossible with the current group size The impossibility may be subtle and diffuse –think of an overconstrained system of equations

Equilibrium Analysis Have a complex system of interacting individuals –each with his or her own preferences, desires, goals, etc. –each adjusting their behavior in response to others –each trying to selfishly improve their own situation Equilibrium: –a global situation (choice of individual behaviors)… –… in which no individual wants to change their behavior unilaterally A stable state or fixed point of the behavioral dynamics Not necessarily desirable: –for individuals –for the global population –just a situation nothing can do anything about (by themselves) But without equilibria, it’s difficult to –describe how the system will evolve –judge the goodness or badness of collective outcomes –discuss how we might influence collective outcomes

Roadmap: Next ~5 Weeks “Micromotives and Macrobehavior” (Schelling): –market economies vs. more general social systems –tipping and cascading in social systems Game Theory and Economics: –generalization and formalization of equilibrium notions –Nash, correlated, market, and other equilibria –games and markets on networks Interdependent Security Games –tipping and cascading in airline security –influence of network structure Behavioral Game Theory –merging psychology with economics –network effects Evolutionary Game Theory –optimize or mimic?

Schelling Quotes On the amorality of equilibrium analysis: –“The body of a hanged man is in equilibrium when it stops swinging, but nobody is going to insist that the man is all right.” On contingent and interdependent behavior: –“If your problem is that there is too much traffic, you are part of the problem.” On the open-ended influence of apparently closed markets: –“The market for pets does not reflect the interest of bird lovers in the market for cats.” On inescapable “accounting identities” : –“Any one of us can get rid of Canadian quarters by passing them on, but collectively we cannot.”

Schelling’s Morals Generalized social systems vs. economics –economics is special case of voluntary participation –but both share many important concepts --- e.g. equilibrium analysis Cannot infer individual preferences from global outcome –due to frequent unilateral nature of equilibrium/outcome –individuals may be “trapped in the system” Global outcome may violate everyone’s common wishes –we might all be trapped –then how did we get here, and why can’t we escape? The prevalence of critical mass phenomena –what happens when not enough or too many engage in some behavior Social systems often show cascading and tipping –we become trapped by incremental, myopic, self-interested behavior –final can be highly influenced by initial conditions

The Market for Lemons People who are selling bad used cars know it People who are buying used cars don’t know which are bad Buyers average (expected) fraction of lemons into prices –a low price for a good car  discourages sellers of good cars –a high price for a lemon  encourages sellers of lemons So, the fraction of lemons increases Now even average cars are undervalued and leave market Which means an even higher fraction of lemons, etc. Note: evolution occurs even if lemons are initially rare! Generalizes to many settings with asymmetric information: –insurance companies and people with diseases, suicidal tendencies,… Market may unravel entirely due to such processes

Volleyball, Critical Mass and Tipping Consider activities where the number who will participate depends on the (expected) number participating Schelling’s examples: volleyball and seminars –but also going to the movies, Internet downloads, voting,… –“individuals” may be (e.g.) computer programs May prefer crowds, solitude, or some precise balance Different people may have different preferences Dynamics can often be conceptualized in a diagramdiagram To compute what will happen from a given starting point: –go up to the curve from the starting point –go from current point on curve horizontally (left or right) to diagonal –go from diagonal vertically (up or down) back to curve –keep repeating last two steps Can get equilibria (stable or unstable), cycles (limited or not)

Local Preferences and Segregation Special case of preferences: housing choices Imagine individuals who are either “red” or “blue” They live on in a grid world with 8 neighboring cells Neighboring cells either have another individual or are empty Individuals have preferences about demographics of their neighborhood Here is a very nice simulatorsimulator