This paper examines how game theory has been applied to real-world problems, focusing on three distinct domains: cloud computing resource allocation, the Monty Hall probability puzzle, and academic dishonesty in student teams. The paper defines what it means to apply a theory to an actual situation, then critically evaluates whether these applications rest on accurate understandings of game theory, whether they exceed the theory's legitimate claims, and whether the reasoning linking theory to application is sound. Drawing on studies by Wei et al. (2010), Kunsemoller and Holger (2012), Yolken and Bambos (2011), Gill (2011), and Briggs et al. (2012), the paper finds both exemplary and overreaching uses of game-theoretic modeling.
The application of game theory involves analyzing situations in which players respond differently according to the actions of other players in an effort to maximize their payouts. According to Wei, Vasilakos, Zheng, and Xiong (2010), "Game theory studies the problems in which players maximize their returns which depend also on actions of other players" (p. 254). Because countless human experiences involve this type of analysis, it is not surprising that game theory has been applied to a wide range of scenarios involving the identification of optimal decision-making processes. In this regard, Wei et al. (2010) advise, "Numerous studies have proposed game-theoretic method to solve the optimization problem of resource allocation in network systems from the viewpoint of resource owners" (p. 254).
One such study, "A Game-Theoretical Approach to the Benefits of Cloud Computing" by Kunsemoller and Holger (2012), applies a game-theoretical model that closely mirrors the Monty Hall Problem's (MHP) choice scenario. The interaction model developed by Kunsemoller and Holger (2012) "maps both contractors' courses of action using game theory" with the goal of estimating future pricing (p. 150). The model provides for the first player — the client — to either use the cloud or build its own data center. The opposing player, the cloud provider, offers three different pricing regimens with corresponding payoffs (Kunsemoller & Holger, 2012). As with the MHP, the final round of the contest allows the first player a subsequent choice to accept or decline an offer: "An extensive form game is used, as the provider is making its offer and subsequently the client is free to accept it or not" (Kunsemoller & Holger, 2012, p. 150).
Applying a theory to a real-world problem or situation means that people besides the researchers will be involved — an eventuality that inevitably introduces numerous confounding factors. In this case, applying game theory to a real-world problem can help illuminate what truly motivates people to behave as they do in settings with dynamic features. For example, according to Gill (2011), "Game theory gives a more suitable framework in which to represent our ignorance of the mechanics of the set-up (where the car is hidden) and of the mechanics of the host's choice, than subjectivist probability" (p. 59). In some cases, researchers apply game theory appropriately; in others, they stretch the boundaries of the theory to include so many extraneous factors that the analysis becomes non-game-theoretic in nature.
In many cases, researchers present a comprehensive and thorough understanding of game theory and its scope. For instance, a study by Yolken and Bambos (2011) provides an interactive pricing and allocation model for utility computing resources. The model assumes that client tasks are represented as job flows in a controlled queuing system that draws on game theory. According to the Yolken and Bambos model, "These jobs arrive to the system through a fixed, random process, are stored in a buffer, and then are serviced by the resource in a first come, first served manner" (2011, p. 166). The model is interactive in that it allows for an ongoing evaluation of pricing schemes based on current aggregate bid patterns among system users.
In this regard, Yolken and Bambos note that "the service rate, however, is set through an auction-like, proportional share mechanism — users submit bids to the system operator and then receive service which is a function of their bids and the bids of the other users. Clients, therefore, must balance the delay experienced by their jobs vs. the added cost of buying additional resource capacity" (2011, p. 166). Taken together, this application of game theory is premised upon an accurate understanding of the theory and its scope, as reflected by the authors' observation that "using ideas from game theory, we show that such a scheme has a unique Nash Equilibrium and moreover that this point can be reached in a distributed, asynchronous manner" (Yolken & Bambos, 2011, p. 166).
"Gill's Monty Hall analysis stretches game theory's predictive claims"
"Rational choice model explains team cheating incentives"
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