In a social network, agents are intelligent and have the capability to make decisions to maximize their utilities. They can either make wise decisions by taking advantages of other agents’ experiences through learning, or make decisions earlier to avoid competitions from huge crowds. Both these two effects, social learning and negative network externality, play important roles in the decision process of an agent. While there are existing works on either social learning or negative network externality, a general study on considering both these two contradictory effects is stil l limited. We find that the Chinese restaurant process, a popular random process, provides a well-defined s tructure to model the decision process of an agent under these two effects. By introducing the strategic behavior into the non-strategic Chinese restaurant process, in Part I of this two-part paper, we prop ose a new game, called Chinese Restaurant Game, to formulate the social learning problem with negative network externality. Through analyzing the proposed Chinese restaurant game, we derive the optimal strategy of each agent and provide a recursive method to achieve the optimal strategy. How social learning and negative network externality influence each other under various settings is also studied through si mulations.
A closely-related strategic game model to our work is the global game @cite_19 @cite_22 . In the global game, all agents, with limited knowledge on the system state and information hold by other agents, make decisions simultaneously. The agent's reward in the game is determined by the system state and the number of agents making the same decision with him. The influence may be positive or negative depending on the type of network externality. An important characteristics of global game is that the equilibrium is unique, which simplifies the discussion on the possible outcome of the game. It draws great attentions in various research fields, such as financial crisis @cite_14 , sensor networks @cite_3 and cognitive radio networks @cite_18 . Since all players in the global game make decisions simultaneously, there is no learning involved in the global game.
@cite_18 @cite_14 @cite_22 @cite_3 @cite_19
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This paper studies decentralized dynamic spectrum access using the theory of multivariate global games. We consider a network of cognitive radios (CRs) where each CR obtains noisy multivariate measurements of the quality of several logical channels and needs to decide which channel to access. Assuming the CRs are rational devices, each CR determines which channel to access, based on its expected throughput and Bayesian estimate of the intention of other CRs. We formulate conditions for which the Bayesian Nash equilibrium (BNE) of the resulting global game is monotonically increasing in the quality of the logical channel. This leads to a simple characterization of the competitive optimal behavior of the system as a function of the prior probability distribution of spectrum hole occupancy, channel quality and observation noise. In obtaining the characterization of the BNE, we extend recent results in univariate global games to the multivariate case. Many argue that crises -- such as currency attacks, bank runs and riots -- can be described as times of non-fundamental volatility. We argue that crises are also times when endogenous sources of information are closely monitored and thus an important part of the phenomena. We study the role of endogenous information in generating volatility by introducing a financial market in a coordination game where agents have heterogeneous information about the fundamentals. The equilibrium price aggregates information without restoring common knowledge. In contrast to the case with exogenous information, we find that uniqueness may not be obtained as a perturbation from common knowledge: multiplicity is ensured when individuals observe fundamentals with small idiosyncratic noise. Multiplicity may emerge also in the financial price. When the equilibrium is unique, it becomes more sensitive to non-fundamental shocks as private noise is reduced. Global games are games of incomplete information whose type space is determined by the players each observing a noisy signal of the underlying state. With strategic complementarities, global games often have a unique, dominance solvable equilibrium, allowing analysis of a number of economic models of coordination failure. For symmetric binary action global games, equilibrium strategies in the limit (as noise becomes negligible) are simple to characterize in terms of 'diffuse' beliefs over the actions of others. We describe a number of economic applications that fall in this category. We also explore the distinctive roles of public and private information in this setting, review results for general global games, discuss the relationship between global games and a literature on higher order beliefs in game theory and describe the relationship to local interaction games and dynamic games with payoff shocks. This paper considers two methodologies for decentralized sensor activation in wireless sensor networks for energy-efficient monitoring. First, decentralized activation in wireless sensor networks is investigated using the theory of global games. Given a large number of sensors which can operate in either an energy-efficient ''low-resolution'' monitoring mode, or a more costly ''high-resolution'' mode, the problem of computing and executing a strategy for mode selection is formulated as a global game with diverse utilities and noise conditions. We formulate Bayes-Nash equilibrium conditions for which a simple threshold strategy is competitively optimal for each sensor, and propose a scheme for decentralized threshold computation. The second class of results we consider is in a non-Bayesian context where sensors deploy simple adaptive filtering algorithms and the global behavior converges to the set of correlated equilibria. A global game is an incomplete information game where the actual payoff structure is determined by a random draw from a given class of games and where each player makes a noisy observation of the selected game. For 2 x 2 games, it is shown that, when the noise vanishes, iterated elimination of dominated strategies in the global game forces the players to conform to J. C. Harsanyi and R. Selten's risk dominance criterion. Copyright 1993 by The Econometric Society.