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Games, Volume 2, Issue 1 (March 2011), Pages 1-199

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Open AccessArticle Cycles of Conditional Cooperation in a Real-Time Voluntary Contribution Mechanism
Games 2011, 2(1), 1-15; doi:10.3390/g2010001
Received: 30 September 2010 / Revised: 14 December 2010 / Accepted: 4 January 2011 / Published: 14 January 2011
Cited by 2 | PDF Full-text (206 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper provides a new way to identify conditional cooperation in a real-time version of the standard voluntary contribution mechanism. We define contribution cycles as the number of contributors a player waits for before committing to a further contribution, and use a [...] Read more.
This paper provides a new way to identify conditional cooperation in a real-time version of the standard voluntary contribution mechanism. We define contribution cycles as the number of contributors a player waits for before committing to a further contribution, and use a permutation test on contribution cycles to assign a measure of conditional cooperation to each group play. The validity of the measures is tested in an experiment. We find that roughly 20% of the plays exhibit dynamics of conditional cooperation. Moreover, notwithstanding a decline in contributions, conditional cooperation is found to be stable over time. Full article
Open AccessArticle Intergroup Prisoner’s Dilemma with Intragroup Power Dynamics
Games 2011, 2(1), 21-51; doi:10.3390/g2010021
Received: 2 November 2010 / Revised: 6 January 2011 / Accepted: 3 February 2011 / Published: 8 February 2011
Cited by 10 | PDF Full-text (2612 KB) | HTML Full-text | XML Full-text
Abstract
The Intergroup Prisoner’s Dilemma with Intragroup Power Dynamics (IPD^2) is a new game paradigm for studying human behavior in conflict situations. IPD^2 adds the concept of intragroup power to an intergroup version of the standard Repeated Prisoner’s Dilemma game. We conducted a [...] Read more.
The Intergroup Prisoner’s Dilemma with Intragroup Power Dynamics (IPD^2) is a new game paradigm for studying human behavior in conflict situations. IPD^2 adds the concept of intragroup power to an intergroup version of the standard Repeated Prisoner’s Dilemma game. We conducted a laboratory study in which individual human participants played the game against computer strategies of various complexities. The results show that participants tend to cooperate more when they have greater power status within their groups. IPD^2 yields increasing levels of mutual cooperation and decreasing levels of mutual defection, in contrast to a variant of Intergroup Prisoner’s Dilemma without intragroup power dynamics where mutual cooperation and mutual defection are equally likely. We developed a cognitive model of human decision making in this game inspired by the Instance-Based Learning Theory (IBLT) and implemented within the ACT-R cognitive architecture. This model was run in place of a human participant using the same paradigm as the human study. The results from the model show a pattern of behavior similar to that of human data. We conclude with a discussion of the ways in which the IPD^2 paradigm can be applied to studying human behavior in conflict situations. In particular, we present the current study as a possible contribution to corroborating the conjecture that democracy reduces the risk of wars. Full article
(This article belongs to the Special Issue Predicting Behavior in Games)
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Open AccessArticle Toward a Theory of Play: A Logical Perspective on Games and Interaction
Games 2011, 2(1), 52-86; doi:10.3390/g2010052
Received: 25 November 2010 / Revised: 9 February 2011 / Accepted: 11 February 2011 / Published: 16 February 2011
Cited by 14 | PDF Full-text (529 KB) | HTML Full-text | XML Full-text
Abstract
Logic and game theory have had a few decades of contacts by now, with the classical results of epistemic game theory as major high-lights. In this paper, we emphasize a recent new perspective toward “logical dynamics”, designing logical systems that focus on [...] Read more.
Logic and game theory have had a few decades of contacts by now, with the classical results of epistemic game theory as major high-lights. In this paper, we emphasize a recent new perspective toward “logical dynamics”, designing logical systems that focus on the actions that change information, preference, and other driving forces of agency. We show how this dynamic turn works out for games, drawing on some recent advances in the literature. Our key examples are the long-term dynamics of information exchange, as well as the much-discussed issue of extensive game rationality. Our paper also proposes a new broader interpretation of what is happening here. The combination of logic and game theory provides a fine-grained perspective on information and interaction dynamics, and we are witnessing the birth of something new which is not just logic, nor just game theory, but rather a Theory of Play. Full article
(This article belongs to the Special Issue Epistemic Game Theory and Modal Logic)
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Open AccessArticle Nonspecific Networking
Games 2011, 2(1), 87-113; doi:10.3390/g2010087
Received: 27 October 2010 / Revised: 25 January 2011 / Accepted: 15 February 2011 / Published: 17 February 2011
Cited by 1 | PDF Full-text (400 KB) | HTML Full-text | XML Full-text
Abstract
A new model of strategic networking is developed and analyzed, where an agent’s investment in links is nonspecific. The model comprises a large class of games which are both potential and super- or submodular games. We obtain comparative statics results for Nash [...] Read more.
A new model of strategic networking is developed and analyzed, where an agent’s investment in links is nonspecific. The model comprises a large class of games which are both potential and super- or submodular games. We obtain comparative statics results for Nash equilibria with respect to investment costs for supermodular as well as submodular networking games. We also study supermodular games with potentials. We find that the set of potential maximizers forms a sublattice of the lattice of Nash equilibria and derive comparative statics results for the smallest and the largest potential maximizer. Finally, we provide a broad spectrum of applications from social interaction to industrial organization. Full article
Open AccessArticle Do I Really Want to Know? A Cognitive Dissonance-Based Explanation of Other-Regarding Behavior
Games 2011, 2(1), 114-135; doi:10.3390/g2010114
Received: 23 December 2010 / Accepted: 15 February 2011 / Published: 18 February 2011
Cited by 14 | PDF Full-text (241 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We investigate to what extent genuine social preferences can explain observed other-regarding behavior. In a dictator game variant subjects can choose whether to learn about the consequences of their choice for the receiver. We find that a majority of subjects showing other-regarding [...] Read more.
We investigate to what extent genuine social preferences can explain observed other-regarding behavior. In a dictator game variant subjects can choose whether to learn about the consequences of their choice for the receiver. We find that a majority of subjects showing other-regarding behavior when the payoffs of the receiver are known, choose to ignore these consequences if possible. This behavior is inconsistent with preferences about outcomes. Other-regarding behavior may also be explained by avoiding cognitive dissonance as in Konow (2000). Our experiment’s choice data is in line with this approach. In addition, we successfully relate individual behavior to proxies for cognitive dissonance. Full article
Open AccessArticle A Loser Can Be a Winner: Comparison of Two Instance-based Learning Models in a Market Entry Competition
Games 2011, 2(1), 136-162; doi:10.3390/g2010136
Received: 21 December 2010 / Revised: 1 March 2011 / Accepted: 14 March 2011 / Published: 16 March 2011
Cited by 12 | PDF Full-text (163 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a case of parsimony and generalization in model comparisons. We submitted two versions of the same cognitive model to the Market Entry Competition (MEC), which involved four-person and two-alternative (enter or stay out) games. Our model was designed according [...] Read more.
This paper presents a case of parsimony and generalization in model comparisons. We submitted two versions of the same cognitive model to the Market Entry Competition (MEC), which involved four-person and two-alternative (enter or stay out) games. Our model was designed according to the Instance-Based Learning Theory (IBLT). The two versions of the model assumed the same cognitive principles of decision making and learning in the MEC. The only difference between the two models was the assumption of homogeneity among the four participants: one model assumed homogeneous participants (IBL-same) while the other model assumed heterogeneous participants (IBL-different). The IBL-same model involved three free parameters in total while the IBL-different involved 12 free parameters, i.e., three free parameters for each of the four participants. The IBL-different model outperformed the IBL-same model in the competition, but after exposing the models to a more challenging generalization test (the Technion Prediction Tournament), the IBL-same model outperformed the IBL-different model. Thus, a loser can be a winner depending on the generalization conditions used to compare models. We describe the models and the process by which we reach these conclusions. Full article
(This article belongs to the Special Issue Predicting Behavior in Games)
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Open AccessArticle A Scent of Lemon—Seller Meets Buyer with a Noisy Quality Observation
Games 2011, 2(1), 163-186; doi:10.3390/g2010163
Received: 17 November 2010 / Revised: 8 February 2011 / Accepted: 14 March 2011 / Published: 18 March 2011
Cited by 4 | PDF Full-text (348 KB) | HTML Full-text | XML Full-text
Abstract
We consider a market for lemons in which the seller is a monopolistic price setter and the buyer receives a private noisy signal of the product’s quality. We model this as a game and analyze perfect Bayesian equilibrium prices, trading probabilities and [...] Read more.
We consider a market for lemons in which the seller is a monopolistic price setter and the buyer receives a private noisy signal of the product’s quality. We model this as a game and analyze perfect Bayesian equilibrium prices, trading probabilities and gains of trade. In particular, we vary the buyer’s signal precision, from being completely uninformative, as in standard models of lemons markets, to being perfectly informative. We show that high quality units are sold with positive probability even in the limit of uninformative signals, and we identify some discontinuities in the equilibrium predictions at the boundaries of completely uninformative and completely informative signals, respectively. Full article
Open AccessArticle Bounded Memory, Inertia, Sampling and Weighting Model for Market Entry Games
Games 2011, 2(1), 187-199; doi:10.3390/g2010187
Received: 3 January 2011 / Revised: 8 March 2011 / Accepted: 16 March 2011 / Published: 21 March 2011
Cited by 8 | PDF Full-text (164 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes the “Bounded Memory, Inertia, Sampling and Weighting” (BI-SAW) model, which won the http://sites.google.com/site/gpredcomp/Market Entry Prediction Competition in 2010. The BI-SAW model refines the I-SAW Model (Erev et al. [1]) by adding the assumption of limited memory span. In particular, [...] Read more.
This paper describes the “Bounded Memory, Inertia, Sampling and Weighting” (BI-SAW) model, which won the http://sites.google.com/site/gpredcomp/Market Entry Prediction Competition in 2010. The BI-SAW model refines the I-SAW Model (Erev et al. [1]) by adding the assumption of limited memory span. In particular, we assume when players draw a small sample to weight against the average payoff of all past experience, they can only recall 6 trials of past experience. On the other hand, we keep all other key features of the I-SAW model: (1) Reliance on a small sample of past experiences, (2) Strong inertia and recency effects, and (3) Surprise triggers change. We estimate this model using the first set of experimental results run by the competition organizers, and use it to predict results of a second set of similar experiments later ran by the organizers. We find significant improvement in out-of-sample predictability (against the I-SAW model) in terms of smaller mean normalized MSD, and such result is robust to resampling the predicted game set and reversing the role of the sets of experimental results. Our model’s performance is the best among all the participants. Full article
(This article belongs to the Special Issue Predicting Behavior in Games)

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Open AccessShort Note Correlated Individual Differences and Choice Prediction
Games 2011, 2(1), 16-20; doi:10.3390/g2010016
Received: 17 December 2010 / Revised: 14 January 2011 / Accepted: 26 January 2011 / Published: 7 February 2011
PDF Full-text (182 KB) | HTML Full-text | XML Full-text
Abstract
This note briefly summarizes the consequences of adding correlated individual differences to the best baseline model in the Games competition, I-SAW. I find evidence that the traits of an individual are correlated, but refining I-SAW to capture these correlations does not significantly [...] Read more.
This note briefly summarizes the consequences of adding correlated individual differences to the best baseline model in the Games competition, I-SAW. I find evidence that the traits of an individual are correlated, but refining I-SAW to capture these correlations does not significantly improve the model’s accuracy when predicting average behavior. Full article
(This article belongs to the Special Issue Predicting Behavior in Games)

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