pushing the envelope: new research topics at the interface of cs and econ/gt
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Pushing the Envelope: new research topics at the interface of cs and econ/gt. Yoav Shoham Stanford University (many debts are due). Primary areas of interaction so far. Computing solution concepts, primarily NE Multi-agent learning - PowerPoint PPT PresentationTRANSCRIPT
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Pushing the Envelope:new research topics at the interface of cs and econ/gt
Yoav Shoham
Stanford University
(many debts are due)
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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
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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
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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)
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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)
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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
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Stanford, April 2007 BAGT Symposium 7
Some Intuition about Learning
Left Right
Up 1,0 3,2
Down 2,1 4,0
Stackelberg Game
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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
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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.
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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
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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
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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?
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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
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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]
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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
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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
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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”
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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
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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
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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
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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.
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Stanford, April 2007 BAGT Symposium 23
Tournament auction
Other activities added to basic tournament auction
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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.
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Stanford, April 2007 BAGT Symposium 25
Average Price Game
The consumer who bids closest to the average of all bids wins the
prize.
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Stanford, April 2007 BAGT Symposium 26
Team Bidding
Bidders form teams and pool their bids.
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Stanford, April 2007 BAGT Symposium 27
… Cariocas’ Community Auction
A “global bid” triggers the close
of multiple auctions.
Community Auction
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Stanford, April 2007 BAGT Symposium 28
Online collectibles
Online collection of digital objects, initially assembled by various
online activities.
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Stanford, April 2007 BAGT Symposium 29
Online collectibles
… and then exchanged via online
barter
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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
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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
![Page 31: Pushing the Envelope: new research topics at the interface of cs and econ/gt](https://reader036.vdocument.in/reader036/viewer/2022070403/56813a0e550346895da1e32f/html5/thumbnails/31.jpg)
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.
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Stanford, April 2007 BAGT Symposium 33
Formal Model, continued
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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
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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
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Stanford, April 2007 BAGT Symposium 36
thank you!