Authors:ANDRÉ BARREIRA DA SILVA ROCHA Abstract: Advances in Complex Systems, Ahead of Print. I study two mechanisms based on punishment to promote cooperation in the well-mixed two-population snowdrift game (SG). The first mechanism follows a standard approach in the literature and is based on the inclusion of a third additional pure strategy in the payoff matrix of the stage-game. Differently, the second mechanism consists of letting cooperators punish defectors with a given exogenous frequency. In the latter, the pure strategy cooperation is replaced by a mixed strategy in which cooperators randomize between cooperation and punishment against defectors. While both mechanisms share the same result regarding the minimum required level of punishment in order to eliminate defectors in both populations, stability in the mechanism following the second approach is more robust in the sense that extinction of defectors is a globally asymptotically stable state for any interior initial conditions in the phase space. Thus, the second mechanism displays a topologically simpler model but the robustness of the evolutionary equilibrium is improved. Results were obtained analytically through nonlinear differential equations and also using an agent-based simulation. There was a good level of agreement between both approaches with respect to the evolutionary pattern over time and the possible steady-states. Citation: Advances in Complex Systems PubDate: 2017-09-20T03:26:14Z DOI: 10.1142/S0219525917500102

Authors:J. DE ABREU, P. GARCÍA, J. GARCÍA Abstract: Advances in Complex Systems, Ahead of Print. In this work, we introduce a deterministic scheme of synchronization of nonlinear cellular automata with chaotic behavior, connected through a master–slave coupling. By using a definition of Boolean derivative, we utilize the linear approximation of the cellular automata rules to design a deterministic and simple coupling function that ensures synchronization. Our results show that it is possible to synchronize nonlinear chaotic cellular automata using a deterministic coupling function that does not introduce into the slave all the information about the state of the master. Citation: Advances in Complex Systems PubDate: 2017-08-29T07:25:25Z DOI: 10.1142/S0219525917500060

Authors:DINGJIE WANG, XIUFEN ZOU Abstract: Advances in Complex Systems, Ahead of Print. The controllability of multilayer networks has become increasingly important in many areas of science and engineering. In this paper, we identify the general rules that determine the controllability and control energy cost of multilayer networks. First, we quantitatively estimate the control energy cost of multilayer networks and investigate the impacts of different coupling strength and coupling patterns on the control energy cost for multilayer networks. The results indicate that the average energy and the coupling strength have an approximately linear relationship in multilayer networks with two layers. Second, we study how the coupling strength and the connection patterns between different layers affect the controllability of multilayer networks from both theoretical and numerical aspects. The obtained piecewise functional relations between the controllability’s measure and coupling strength reveal the existence of an optimal coupling strength for the different interconnection strategies in multilayer networks. In particular, the numerical experiments demonstrate that there exists a tradeoff between the optimal controllability and optimal control energy for selecting interlayer connection patterns in multilayer networks. These results provide a comprehensive understanding of the impact of interlayer couplings on the controllability and control energy cost for multilayer networks and provide a methodology for selecting the control nodes and coupling strength to maximize the controllability and minimize the control energy cost. Citation: Advances in Complex Systems PubDate: 2017-08-29T07:25:24Z DOI: 10.1142/S0219525917500084

Authors:MATTHEW OLDHAM Abstract: Advances in Complex Systems, Ahead of Print. The inability of investors and academics to consistently predict, and understand the behavior of financial markets has forced the search for alternative analytical frameworks. Analyzing financial markets as complex systems is a framework that has demonstrated great promises, with the use of agent-based models (ABMs) and the inclusion of network science playing an important role in increasing the relevance of the framework. Using an artificial stock market created via an ABM, this paper provides a significant insight into the mechanisms that drive the returns in financial markets, including periods of elevated prices and excess volatility. The paper demonstrates that the network topology that investors form and the dividend policy of firms significantly affect the behavior of the market. However, if investors have a bias to following their neighbors then the topology becomes redundant. By successfully addressing these issues this paper helps refine and shape a variety of additional research tasks for the use of ABMs in uncovering the dynamics of financial markets. Citation: Advances in Complex Systems PubDate: 2017-08-29T07:25:23Z DOI: 10.1142/S0219525917500072

Authors:FRIEDERIKE WALL Abstract: Advances in Complex Systems, Ahead of Print. The paper studies which incentive systems emerge in organizations when self-interested managers collaboratively search for higher levels of organizational performance and the headquarters learn about the success of the incentive systems employed. The study uses an agent-based simulation and, in particular, controls for different levels of intra-organizational complexity and modes of coordination, i.e., the way how preferences on the departmental site are aligned with each other in respect to the overall organizational objective. The results indicate that for different levels of intra-organizational complexity different incentive systems emerge: With lower intra-organizational complexity, in tendency, the less focus is put on firm performance and vice versa. However, results also suggest that the mode of coordination may considerably affect the emergence of the incentive structure. This provides support for the idea that multiple management controls, like the incentive system and the mode of coordination, should be regarded and designed as a system with interrelations among its components and not just as a collection of several control practices. Citation: Advances in Complex Systems PubDate: 2017-07-24T09:01:56Z DOI: 10.1142/S0219525917500035

Authors:PIERFRANCESCO DOTTA, MARCO TOLOTTI, JORGE YEPEZ Abstract: Advances in Complex Systems, Ahead of Print. Brand awareness is recognized to be an important determinant in shaping the success of durables [13, 16], yet it is very difficult to be quantified. This is exactly the main goal of this paper: propose a suitable model where brand awareness of two competing firms is modeled and, eventually, estimated. To this aim, we build a random utility model for a duopoly where each competitor is characterized by different pricing strategies and brand awareness. As a result, different levels of market shares will emerge at the equilibrium. As a case study, we calibrate the model with real data from the smartphone industry obtaining an estimate of the value of the brand awareness of two leading brands. Citation: Advances in Complex Systems PubDate: 2017-07-12T07:34:48Z DOI: 10.1142/S0219525917500047

Authors:KAZUTO SASAI, YUKIO-PEGIO GUNJI, TETSUO KINOSHITA Abstract: Advances in Complex Systems, Ahead of Print. Continuous asynchronous trading activity is a key to understanding real-world market behavior. However, it is not easy to implement an agent-based computational market model because of the ambiguity between time and space. In this study, we use a model of asynchrony in a continuous double auction market in the form of noise and order restrictions to link inside- and outside- uncertainties in the economic system. Our model shows intermittent behavior with a small parameter value, which leads to the misapplication of the price-update rule, and consequently drives burst behavior. The statistical property of time development shows a similar tendency to that in previous empirical studies. Thus, it demonstrates the relationship between the asynchronous property and the complexity of economic systems. Citation: Advances in Complex Systems PubDate: 2017-07-11T06:29:28Z DOI: 10.1142/S0219525917500059