Game Networks

We introduce Game networks (G nets), a novel representation for multi-agent decision problems. Compared to other game-theoretic representations, such as strategic or extensive forms, G nets are more structured and more compact; more fundamentally, G nets constitute a computationally advantageous framework for strategic inference, as both probability and utility independencies are captured in the structure of the network and can be exploited in order to simplify the inference process. An important aspect of multi-agent reasoning is the identification of some or all of the strategic equilibria in a game; we present original convergence methods for strategic equilibrium which can take advantage of strategic separabilities in the G net structure in order to simplify the computations. Specifically, we describe a method which identifies a unique equilibrium as a function of the game payoffs, and one which identifies all equilibria.Comment: Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000

The social context of school playground games: Sex and ethnic differences, and changes over time after entry to junior school

This short term longitudinal study examined activities at recess and peer relations. Interest was in changes over the school year, and the sex and ethnic mix of groups. Data came from systematic observations of 129 pupils (61 boys and 68 girls) aged 7-8 years. Results showed that peer interaction dominated recess. Ball games increased over the year, and chasing games decreased. Aggression was most common during vigorous play and conversation, but not ball games. Cleavage in boys' and girls' play and activity was common but not inevitable. Mixed sex play was not supported by particular game types. Boys’ game networks were larger than those of girls but there were no sex differences in active networks. There was little ethnic group segregation on playgrounds, and games became more integrated with time. Results indicate that playground activities can have a positive role in social relations between different ethnic groups

Endogenous network formation in patent contests and its role as a barrier to entry

In a setting of R&D co-opetition we study, by using an all-pay auction approach, how collaboration affects strategic decisions during a patent contest, and how the latter influences the possible collaboration network structures the firms can hope to form. The all pay auction approach allows us to 1) endogenize both network formation and R&D intensities and 2) take heterogeneous and private valuations for patents into account. We find that, different from previous literature, the complete network is not always the only pairwise stable network, even and especially if the benefits from cooperating are important. Interestingly, the other possible stable networks all have the realistic property that some firms decide not to participate in the contest. Thus, weak cooperation through network formation can serve as a barrier to entry on the market for innovation. We further show that there need not be any network that survives a well known refinement of pairwise stability, strong stability, which imposes networks to be immune to coalitional deviations.patent game, networks, R&D cooperation, all-pay auction

Marketing Strategies for Online Entertainment: A Snapshot of Computer Game Networks

Online entertainment is projected to be a billion dollar industry by the year 2000 (I/PRO, 1996b). Today, however, only a few companies are willing to risk investing in online entertainment. Computer game networks, an infant industry, are one of the rare group of companies taking that risk. Their success depends in large part on how well they market their products and services to their target audience. They are currently targeting Rogers\u27 (1995) Innovators (hard core gamers) primarily with pull technologies. However, financial success will depend on a) targeting the next segment of adopters, Early Adopters, who will be more oriented toward traditional push technologies, and b) retaining innovators by applying new marketing (and product) paradigms

Distinguishing humans from computers in the game of go: a complex network approach

We compare complex networks built from the game of go and obtained from databases of human-played games with those obtained from computer-played games. Our investigations show that statistical features of the human-based networks and the computer-based networks differ, and that these differences can be statistically significant on a relatively small number of games using specific estimators. We show that the deterministic or stochastic nature of the computer algorithm playing the game can also be distinguished from these quantities. This can be seen as tool to implement a Turing-like test for go simulators.Comment: 7 pages, 6 figure

Modeling Paying Behavior in Game Social Networks

Online gaming is one of the largest industries on the Internet, generating tens of billions of dollars in revenues annually. One core problem in online game is to find and convert free users into paying customers, which is of great importance for the sustainable development of almost all online games. Although much research has been conducted, there are still several challenges that remain largely unsolved: What are the fundamental factors that trigger the users to pay? How does users? paying behavior influence each other in the game social network? How to design a prediction model to recognize those potential users who are likely to pay? In this paper, employing two large online games as the basis, we study how a user becomes a new paying user in the games. In particular, we examine how users' paying behavior influences each other in the game social network. We study this problem from various sociological perspectives including strong/weak ties, social structural diversity and social influence. Based on the discovered patterns, we propose a learning framework to predict potential new payers. The framework can learn a model using features associated with users and then use the social relationships between users to refine the learned model. We test the proposed framework using nearly 50 billion user activities from two real games. Our experiments show that the proposed framework significantly improves the prediction accuracy by up to 3-11% compared to several alternative methods. The study also unveils several intriguing social phenomena from the data. For example, influence indeed exists among users for the paying behavior. The likelihood of a user becoming a new paying user is 5 times higher than chance when he has 5 paying neighbors of strong tie. We have deployed the proposed algorithm into the game, and the Lift_Ratio has been improved up to 196% compared to the prior strategy

Gaming on and off the social graph: the social structure of Facebook games

Games built on Online Social Networks (OSNs) have become a phenomenon since 3rd party developer tools were released by OSNs such as Facebook. However, apart from their explosive popularity, little is known about the nature of the social networks that are built during play. In this paper, we present the findings of a network analysis study carried out on two Facebook applications, in comparison with a similar but stand-alone game. We found that games built both on and off a social graph exhibit similar social properties. Specifically, the distribution of player-to-player interactions decays as a power law with a similar exponent for the majority of players. For games built on the social network platform however, we find that the networks are characterised by a sharp cut-off, compared with the classically scale-free nature of the social network for the game not built on an existing social graph

The Medial Turn in Knowledge Society

Many discourses tend to consider change in techniques as the main trigger for social change and economic development. This paper proposes the original hypothesis that the development of new techniques occurs at the end of a long lasting societal process, not as its cause. The rising of the knowledge society since the 17th century is engaged today in what we called the medial turn – defined as a cultural shift through the generalized digital communication. This process is the conclusive stage in the modernization process of societies conceived as positive-sum-game networks. Based on MacLuhan’s famous idea that the “medium is the message”, we address a few questions specialists and engineers are to be confronted to in the medial age