Game Theoretic Aspect in Human Computation Presenter: Chien-Ju Ho

Outline  Human computation Examples Rethinking the ESP Game  Game theoretic analysis Background knowledge of game theory Example: PhotoSlap  General game modeling Classification of human computational games Discussion of the general game modeling

ESP Game & Peekaboom

Tag a Tune

GWAP – Games With A Purpose 

Is the Game Design Rational?

Rethinking the ESP Game  Technical report of Microsoft Research in September  Target: Google Image Labeler

Rethinking the ESP Game  Shortcomings of the ESP Game Easy words first ○ “building” are preferred than ”terraced house” Tendency to match on colors ○ Over 10% of off-limit labels are colors Information redundancy ○ 81% of images labeled “guy” are labeled “man” ○ 68% of images labeled “clouds” are labeled “sky”

Rethinking the ESP Game  An auto-playing robot Analyze the off-limit words No analysis of the images  Probability of matches 81% for images with at least one off-limit words

Game Theoretic Analysis In Human Computation

Background Knowledge of Game Theory

Prisoner’s Dilemma B Stays SilentB Betrays A Stays SilentA: 6 months B: 6 months A: 10 years B: free A BetraysA: free B: 10 years A: 5 years B: 5 years

Normal-form Game  The elements of a normal-form game Players: (prisoner A, prisoner B) Strategies: (stay silent, betray) Payoff: (sentences) B Stays SilentB Betrays A Stays SilentA: 6 months B: 6 months A: 10 years B: free A BetraysA: free B: 10 years A: 5 years B: 5 years

Nash Equilibrium  Strategy profile: a combination of strategies. ex: (A: betray, B: betray)  Each player has no incentive to change her action under the assumption that all the other players do not change their actions. B Stays SilentB Betrays A Stays SilentA: 6 months B: 6 months A: 10 years B: free A BetraysA: free B: 10 years A: 5 years B: 5 years

Extensive Game  Sequential structure of decision-making inout fight acquiesce Google: $ 2 b MS: $ 1b Players Payoff Strategies Google: $ 0 MS: $ 0 Google: $ 1b MS: $ 2b

Subgame Perfect Equilibrium  Play in each subgame is a Nash equilibrium.  (in, acquiesce): A subgame perfect equilibrium

PhotoSlap  A Multi-player game for face recognition

The Game Rule  Slapping on matching pairs Slap The first player who slapped get 100 points.

The Game Rule  Slapping on matching pairs The first player who slapped get 100 points. Slap

The Game Rule  Objecting on un-matched pairs Slap The first player who object get 100 points. The player who slapped lose 100 points.

The Game Rule  Objecting on un-matched pairs The first player who object get 100 points. The player who slapped lose 100 points.

The Game Rule  Setting traps on matching pairs The player who set the trap get 50 points. The player who objected lose 1000 points. Trap Slap

The Game Rule  Setting traps on matching pairs Get 50 points if the trap pair is slapped. Lose 50 points if the trap pair appears but not slapped.

Game Theoretic Analysis Payoff of player 1 Payoff of (player 2, player 3) Chance node For each photo pair in the trap page For each photo pair in the game page Player node The player who sets the trap The player who slaps first The player who objects first

Subgame Perfect Equilibrium  A solution concept in extensive game TrapSlapObject MatchSetSlapStay No MatchStay Object

Human Computation Modeling

Human Computation  Question and Answer  Human as the algorithm InputOutput

Human Computation  Make the process fun Psychology analysis Implementation dependent

Human Computation  Ensure the correctness of the output Motivate helpful behavior Guarantee high probability of correctness even if some malicious players exist  Apply social validation Gain points when results match Check the results produced by different players

Game Templates (1)  Output agreement

Game Templates (2)  Inversion problem

Game Templates (3)  Input agreement

Verification Mechanism  Simultaneous Verification  Sequential Verification

Simultaneous Verification  Coordination Game  Multiple equilibria Equilibrium selection according to the player’s belief  In the ESP Game Players would choose the words ○ More relevant to the image ○ More generic ABCD A(1, 1)(0, 0) B (1, 1)(0, 0) C (1, 1)(0, 0) D (1, 1)

Sequential Verification

Why Game Theory  A theory for understanding the incentive structure and player strategies of games  Widely used in different domains, including economics and social science

Open Issues  Extension of N-player games  Effect of changing incentive structure  Consideration for malicious players  Different validation mechanisms

Research in Human Computation  Applications and information integration  Repeated labeling problem  Human computation as the correctness measure

References  von Ahn, L. and Dabbish, L Designing games with a purpose. Commun. ACM 51, 8 (Aug. 2008),  Ho, C., Chang, T., and Hsu, J. Y PhotoSlap – a multi-player online game for semantic annotation. AAAI07 (Jul. 2007).  Weber, I., Robertson, S. and Vojnović, M Rethinking the ESP Game. Technical Report, Microsoft Research (Sep. 2008).

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