CPS 570: Artificial Intelligence Game Theory

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Presentation transcript:

CPS 570: Artificial Intelligence Game Theory Instructor: Vincent Conitzer

Is this a “rational” outcome? If not, what is? Penalty kick example probability .7 probability .3 action probability 1 Is this a “rational” outcome? If not, what is? action probability .6 probability .4

0, 0 -1, 1 1, -1 Rock-paper-scissors Column player aka. player 2 (simultaneously) chooses a column 0, 0 -1, 1 1, -1 Row player aka. player 1 chooses a row A row or column is called an action or (pure) strategy Row player’s utility is always listed first, column player’s second Zero-sum game: the utilities in each entry sum to 0 (or a constant) Three-player game would be a 3D table with 3 utilities per entry, etc.

A poker-like game 0, 0 1, -1 .5, -.5 1.5, -1.5 -.5, .5 cc cf fc ff rr “nature” 1 gets King 1 gets Jack cc cf fc ff player 1 player 1 rr 0, 0 1, -1 .5, -.5 1.5, -1.5 -.5, .5 raise check raise check rc player 2 player 2 cr call fold call fold call fold call fold cc 2 1 1 1 -2 1 -1 1

0, 0 -1, 1 1, -1 -5, -5 “Chicken” D S D S D S S D Two players drive cars towards each other If one player goes straight, that player wins If both go straight, they both die D S S D D S 0, 0 -1, 1 1, -1 -5, -5 D not zero-sum S

“2/3 of the average” game Example: Everyone writes down a number between 0 and 100 Person closest to 2/3 of the average wins Example: A says 50 B says 10 C says 90 Average(50, 10, 90) = 50 2/3 of average = 33.33 A is closest (|50-33.33| = 16.67), so A wins

Rock-paper-scissors – Seinfeld variant MICKEY: All right, rock beats paper! (Mickey smacks Kramer's hand for losing) KRAMER: I thought paper covered rock. MICKEY: Nah, rock flies right through paper. KRAMER: What beats rock? MICKEY: (looks at hand) Nothing beats rock. 0, 0 1, -1 -1, 1

-i = “the player(s) other than i” Dominance Player i’s strategy si strictly dominates si’ if for any s-i, ui(si , s-i) > ui(si’, s-i) si weakly dominates si’ if for any s-i, ui(si , s-i) ≥ ui(si’, s-i); and for some s-i, ui(si , s-i) > ui(si’, s-i) -i = “the player(s) other than i” 0, 0 1, -1 -1, 1 strict dominance weak dominance

-2, -2 0, -3 -3, 0 -1, -1 Prisoner’s Dilemma confess don’t confess Pair of criminals has been caught District attorney has evidence to convict them of a minor crime (1 year in jail); knows that they committed a major crime together (3 years in jail) but cannot prove it Offers them a deal: If both confess to the major crime, they each get a 1 year reduction If only one confesses, that one gets 3 years reduction confess don’t confess -2, -2 0, -3 -3, 0 -1, -1 confess don’t confess

“Should I buy an SUV?” -10, -10 -7, -11 -11, -7 -8, -8 cost: 5 cost: 5 purchasing + gas cost accident cost cost: 5 cost: 5 cost: 5 cost: 8 cost: 2 cost: 3 cost: 5 cost: 5 -10, -10 -7, -11 -11, -7 -8, -8

Back to the poker-like game “nature” 1 gets King 1 gets Jack cc cf fc ff player 1 player 1 rr 0, 0 1, -1 .5, -.5 1.5, -1.5 -.5, .5 raise check raise check rc player 2 player 2 cr call fold call fold call fold call fold cc 2 1 1 1 -2 1 -1 1

Iterated dominance 0, 0 1, -1 -1, 1 0, 0 1, -1 -1, 1 Iterated dominance: remove (strictly/weakly) dominated strategy, repeat Iterated strict dominance on Seinfeld’s RPS: 0, 0 1, -1 -1, 1 0, 0 1, -1 -1, 1

“2/3 of the average” game revisited 100 dominated (2/3)*100 dominated after removal of (originally) dominated strategies (2/3)*(2/3)*100 …

Mixed strategies Mixed strategy for player i = probability distribution over player i’s (pure) strategies E.g. 1/3 , 1/3 , 1/3 Example of dominance by a mixed strategy: 3, 0 0, 0 1, 0 1/2 1/2

Nash equilibrium [Nash 1950] A profile (= strategy for each player) so that no player wants to deviate D S 0, 0 -1, 1 1, -1 -5, -5 D S This game has another Nash equilibrium in mixed strategies…

0, 0 -1, 1 1, -1 Rock-paper-scissors Any pure-strategy Nash equilibria? But it has a mixed-strategy Nash equilibrium: Both players put probability 1/3 on each action If the other player does this, every action will give you expected utility 0 Might as well randomize

Nash equilibria of “chicken”… D S 0, 0 -1, 1 1, -1 -5, -5 D S Is there a Nash equilibrium that uses mixed strategies? Say, where player 1 uses a mixed strategy? If a mixed strategy is a best response, then all of the pure strategies that it randomizes over must also be best responses So we need to make player 1 indifferent between D and S Player 1’s utility for playing D = -pcS Player 1’s utility for playing S = pcD - 5pcS = 1 - 6pcS So we need -pcS = 1 - 6pcS which means pcS = 1/5 Then, player 2 needs to be indifferent as well Mixed-strategy Nash equilibrium: ((4/5 D, 1/5 S), (4/5 D, 1/5 S)) People may die! Expected utility -1/5 for each player

2, 2 -1, 0 -7, -8 0, 0 The presentation game Pay attention (A) Do not pay attention (NA) 2, 2 -1, 0 -7, -8 0, 0 Put effort into presentation (E) Do not put effort into presentation (NE) Pure-strategy Nash equilibria: (E, A), (NE, NA) Mixed-strategy Nash equilibrium: ((4/5 E, 1/5 NE), (1/10 A, 9/10 NA)) Utility -7/10 for presenter, 0 for audience

Back to the poker-like game, again “nature” 2/3 1/3 1 gets King 1 gets Jack cc cf fc ff player 1 player 1 1/3 rr 0, 0 1, -1 .5, -.5 1.5, -1.5 -.5, .5 raise check raise check 2/3 rc player 2 player 2 cr call fold call fold call fold call fold cc 2 1 1 1 -2 1 -1 1 To make player 1 indifferent between rr and rc, we need: utility for rr = 0*P(cc)+1*(1-P(cc)) = .5*P(cc)+0*(1-P(cc)) = utility for rc That is, P(cc) = 2/3 To make player 2 indifferent between cc and fc, we need: utility for cc = 0*P(rr)+(-.5)*(1-P(rr)) = -1*P(rr)+0*(1-P(rr)) = utility for fc That is, P(rr) = 1/3

Real-world security applications Milind Tambe’s TEAMCORE group (USC) Airport security Where should checkpoints, canine units, etc. be deployed? Federal Air Marshals Which flights get a FAM? US Coast Guard Which patrol routes should be followed? Wildlife Protection Where to patrol to catch poachers or find their snares?