Pushing the Envelope: new research topics at the interface of cs and econ/gt Yoav Shoham Stanford University (many debts are due)
Mar 27, 2015
Pushing the Envelope:new research topics at the interface of cs and econ/gt
Yoav Shoham
Stanford University
(many debts are due)
Stanford, April 2007 BAGT Symposium 2
Primary areas of interaction so far
• Computing solution concepts, primarily NE
• Multi-agent learning
• Compact games (graphical games, MAIDs, game networks, local-effect games, social networks, …)
• Mechanism design, in particular auctions
Stanford, April 2007 BAGT Symposium 3
Talk Outline
• Computing solution concepts, primarily NE
– The role of NE unclear
• Multi-agent learning
– Ditto
• Compact games (graphical games, MAIDs, game networks, local-effect games, social networks, …)
– Other forms of compactness, and what about coalitional games?
• Mechanism design, in particular auctions
– Behavioral Mechanism design
• Beyond GT: Algorithmic Institutional Design
Stanford, April 2007 BAGT Symposium 4
A game with a trivial, unique NE
Heads Tails
Heads 1,-1 -1,1
Tails -1,1 1,-1
Rock Paper Scissors
Rock 0,0 -1,1 1,-1
Paper 1,-1 0,0 -1,1
Scissors -1,1 1,-1 0,0
Matching Pennies Rochambeau (Rock-Paper-Scissors)
Stanford, April 2007 BAGT Symposium 5
A game with a trivial, unique NE
Heads Tails
Heads 1,-1 -1,1
Tails -1,1 1,-1
Rock Paper Scissors
Rock 0,0 -1,1 1,-1
Paper 1,-1 0,0 -1,1
Scissors -1,1 1,-1 0,0
Matching Pennies Rochambeau (Rock-Paper-Scissors)
(www.worldrps.com)
Stanford, April 2007 BAGT Symposium 6
A game with a trivial, unique NE
Heads Tails
Heads 1,-1 -1,1
Tails -1,1 1,-1
Rock Paper Scissors
Rock 0,0 -1,1 1,-1
Paper 1,-1 0,0 -1,1
Scissors -1,1 1,-1 0,0
Matching Pennies Rochambeau (Rock-Paper-Scissors)
(www.worldrps.com)Lesson: Nash equilibrium not necessarily instructive
Stanford, April 2007 BAGT Symposium 7
Some Intuition about Learning
Left Right
Up 1,0 3,2
Down 2,1 4,0
Stackelberg Game
Stanford, April 2007 BAGT Symposium 8
Some Intuition about Learning
Left Right
Up 1,0 3,2
Down 2,1 4,0
Stackelberg Game
Lesson: can’t separate learning from teaching
Stanford, April 2007 BAGT Symposium 10
Five Distinct Research Agendas in MAL
• Computation: Quick-and-dirty method for (e.g.) NE
• Social science: How people (institutions, animals…) learn.
• Game theory puritanism: Equilibria of learning strategies.
• Distributed control: Learning in common-payoff games.
• Targeted learning: Learning when you have some sense of how your opponents might behave.
Stanford, April 2007 BAGT Symposium 11
Lesson: Need to take NE with a grain of salt
• Beautiful, clever
• Makes it hard to back off from assumptions of perfect rationality; can we have an alternative, “constructive” game theory?
• In any event, “best response” computation merits as much attention as eqm
Stanford, April 2007 BAGT Symposium 12
Talk Outline
• Computing solution concepts, primarily NE
– The role of NE unclear
• Multi-agent learning
– Ditto
• Compact games (graphical games, MAIDs, game networks, local-effect games, social networks, …)
– Other forms of compactness, and what about coalitional games?
• Mechanism design, in particular auctions
– Behavioral Mechanism design
• Beyond GT: Algorithmic Institutional Design
Stanford, April 2007 BAGT Symposium 13
On compact representations
• Compact representations are fine; need more– Programming constructs in strategy descriptions (“programmatic
rationality”)– Partial games (e.g., logic-based game description)
• What about coalitional games?
Stanford, April 2007 BAGT Symposium 14
Marginal Contribution Nets
• Games represented by sets of rules
pattern value
{ a & b & c } 5
• Value of a group S equals the sum of the values of the rules S satisfies
v(S) = r : S satisfies r} v(r)
• Focus on conjunction & negation in pattern
Stanford, April 2007 BAGT Symposium 15
Conciseness of MC-Nets
Theorem MC-Nets generalize the multi-issue representation of [CS04]
Theorem MC-Nets generalize the graphical representation of [DP94]
Stanford, April 2007 BAGT Symposium 16
Computational Leverage
• Shapley value can be efficiently computed in MC-nets
– Exploiting Additivity and Symmetry
• Determining membership in core is hard, but one can determine membership in time exponential in treewidth
– Determining emptiness, or finding an arbitrary member of a non-empty core, are no harder
Stanford, April 2007 BAGT Symposium 17
Talk Outline
• Computing solution concepts, primarily NE
– The role of NE unclear
• Multi-agent learning
– Ditto
• Compact games (graphical games, MAIDs, game networks, local-effect games, social networks, …)
– Other forms of compactness, and what about coalitional games?
• Mechanism design, in particular auctions
– Behavioral Mechanism design
• Beyond GT: Algorithmic Institutional Design
Stanford, April 2007 BAGT Symposium 18
Recall some results from auction theory
• Informal observations– Dutch = First-price, sealed bid– English Second-price, sealed bid (cf. proxy bidding)– Japanese ≠ English– Second-price and Japanese have dominant strategies
• For precise analyses, need to distinguish between– Common values and independent values (winner’s curse)– Risk averse, risk-neutral and risk-seeking bidders
• Formal results speak to:– Whether an auction is “incentive compatible”– Whether the auction is “efficient”– Whether the auction is “revenue maximizing”
Stanford, April 2007 BAGT Symposium 19
Example of BMD: Online marketing
• The X5 story
• What are we optimizing for?
• Behavioral requirements (BMD) (ack: Moshe Tennenholtz)
– # sign-ups
– # return visits (magic number: 5)
– Message injection
– Product education
– Truthful consumer surveys
• Yields a new perspective on existing mechanisms
• Suggests new mechanisms
Stanford, April 2007 BAGT Symposium 20
Some new truths about auctions, from the perspective of marketing
• First-price sealed-bid auction ≠ Dutch auction
• Second-price sealed-bid auction ≠ English auction
• Dominant-strategy mechanisms can be suboptimal
• Barter- and multiple-currency markets might trump markets with universal currency
Stanford, April 2007 BAGT Symposium 21
Some new, marketing-oriented mechanisms
• Tournament auction– Infinitely many equilibria
• Average-price auction– Giving the little guy a chance
• Team bidding– Cooperation
• Community auction– Coopetition
• Online collectibles– The marketing advantages of barter systems
• Preference auction– Win-win for the auctioneer and buyers
Stanford, April 2007 BAGT Symposium 22
Tournament auction
A series of sealed-bid auctions; X% make it to the next day; person with highest remaining points wins.
Stanford, April 2007 BAGT Symposium 23
Tournament auction
Other activities added to basic tournament auction
Stanford, April 2007 BAGT Symposium 24
Inserting a population game into an auction
Capturing information about consumers and their views of others; the latter is particularly truthful.
Stanford, April 2007 BAGT Symposium 25
Average Price Game
The consumer who bids closest to the average of all bids wins the
prize.
Stanford, April 2007 BAGT Symposium 26
Team Bidding
Bidders form teams and pool their bids.
Stanford, April 2007 BAGT Symposium 27
… Cariocas’ Community Auction
A “global bid” triggers the close
of multiple auctions.
Community Auction
Stanford, April 2007 BAGT Symposium 28
Online collectibles
Online collection of digital objects, initially assembled by various
online activities.
Stanford, April 2007 BAGT Symposium 29
Online collectibles
… and then exchanged via online
barter
Stanford, April 2007 BAGT Symposium 30
Main takeaways
• Marketing considerations completely change the rules of the game. Some lessons of BMD:
– new design criteria
– new perspectives on existing mechanisms
– new mechanisms
• Many applications beyond marketing. Example: Captchas, ESP
• A lot more work is needed before this becomes a science
Stanford, April 2007 BAGT Symposium 31
Talk Outline
• Computing solution concepts, primarily NE
– The role of NE unclear
• Multi-agent learning
– Ditto
• Compact games (graphical games, MAIDs, game networks, local-effect games, social networks, …)
– Other forms of compactness, and what about coalitional games?
• Mechanism design, in particular auctions
– Behavioral Mechanism design
• Beyond GT: Algorithmic Institutional Design
Stanford, April 2007 BAGT Symposium 32
Algorithmic Institutional Design (ack: Mike Munie)
• What is better: The EE or CS qual structure at Stanford?
• Similar for job interviews, admissions, consumer surveys, etc
• Reminiscent of, but distinct from, the “secretary problem”
• The answer: Depends on what you’re optimizing for. And even given that, depends.
Stanford, April 2007 BAGT Symposium 33
Formal Model, continued
Stanford, April 2007 BAGT Symposium 34
Results
• Multiple versions– Single prof?– Single student?– Parallel or sequential?
• Sample results– Even in simplest case, selecting an optimal set of questions is NP-
Hard, and is not submodular, so there is a not an obvious approximation algorithm
– Sequentiality can be maximally helpful– In the multiagent setting, even deciding between committee
structures is NP-Hard– *Seems* like there are well behaved special cases
Stanford, April 2007 BAGT Symposium 35
Talk Outline
• Computing solution concepts, primarily NE
– The role of NE unclear
• Multi-agent learning
– Ditto
• Compact games (graphical games, MAIDs, game networks, local-effect games, social networks, …)
– Other forms of compactness, and what about coalitional games?
• Mechanism design, in particular auctions
– Behavioral Mechanism design
• Beyond GT: Algorithmic Institutional Design
Stanford, April 2007 BAGT Symposium 36
thank you!