Amount Of Players Research Articles

Emergence of Altruistic Behavior Based on Game Involves Reputation and Future Expectation in Complex Networks

We study the altruistic behavior on spatial small-world network and scale-free network in the framework of game theory, by establishing a mechanism based on reputation and future expectation. Each player interacts with his immediate neighbors can follow two strategies: cooperation or defection. Reputation and discount factor are respectively introduced to describe the information of players’ historical behavior and the future expectation of players. Players not only consider current payoff but also care about future payoff when they employ strategy. Simulations and analysis show players choose cooperation voluntarily for the purpose of payoff-maximizing as long as the benefit-to-cost ratio is big enough. The level of convergence average reputation of group does not rely on the level of initial average reputation of group absolutely. Group can converge to full cooperation even though the initial average reputation of group is small. In a certain interval, a slight increase of the initial average reputation of group can effectively enhance the level of cooperation. Although the non-subjective factors prevent cooperation from emerging, complex network has a certain ability to resist the disturbance. The cooperation state in scale-free network is more stable than that in small-world network. Concentrating on the situation of group state changing from cooperative to defective, dynamic spatial patterns of small-world network show long-range connections are the main reason for the emergence of new defective cluster. Reasonable network randomness is in favor of motivating altruistic behavior. In scale-free network, heterogeneity makes players converge to three states: full cooperation, full defection and reputation oscillate in a specific domain with particular mode. A small amount of players with large degree and high reputation and a large number of players with small degree and low reputation restrict each other, which enable group can converge to a state between full cooperation and full defection. In addition, heterogeneity has no effect on promoting behavior spread under the mechanism against the common belief.

Sharing the Effort Costs in Collective Contests

This paper analyzes the following two stage contest among two groups for a public good. In the first stage, each group decides how to share the effort costs of the contest among its players. Each group can opt to split equally its total costs among its players, to let that each player bears her own cost, or a convex combination among both. In the second stage, each player exerts effort and the contest takes place. The main findings consist in the fact that when groups are homogenous, each group decides to split equally the total costs among its players. But if groups differ in size, valuations of the prize or individual marginal cost, only the group which has a larger amount of players, a higher valuation of the prize or a lower marginal cost will completely split equally the total costs, while the other group will set a convex combination among both rules. Then, the first group exerts more effort in equilibrium and reduces free riding. I also analyze the case in which players within a group have different abilities, and the cases where the good is private or impurely public.

EXPLORING THE DIMENSIONS OF CONVENTION EMERGENCE IN MULTIAGENT SYSTEMS

Social conventions are useful self-sustaining protocols for groups to coordinate behavior without a centralized entity enforcing coordination. The emergence of such conventions in different multi agent network topologies has been investigated by several researchers, although exploring only specific cases of the convention emergence process. In this work we will provide multi-dimensional analysis of several factors that we believe determines the process of convention emergence, such as: the size of agents memory, the population size and structure, the learning approach taken by agents, the amount of players in the interactions, or the convention search space dimension. Although we will perform an exhaustive study of different network structures, we are concerned that different topologies will affect the emergence in different ways. Therefore, the main research question in this work is comparing and studying effects of different topologies on the emergence of social conventions. While others have investigated memory for learning algorithms, the effects of memory on the reward have not been investigated thoroughly. We propose a reward metric that is derived directly from the history of the interacting agents. Another research question to be answered is what effect does the history based reward function and the learning approach have on convergence time in different topologies. Experimental results show that all the factors analyzed affect differently the convention emergence process, being such information very useful for policy-makers when designing self-regulated systems.

Integration i dansk kvindehåndbold. Slagelse FH og Aalborg DH som cases

Artiklen undersøger med udgangspunkt i Slagelse FH og Aalborg DH, klubbernes strategier for integration af udenlandske spillere.
 
 Sine Agergaard and Line Vindbæk Andersen: Integration in Danish Women Handball. Slagelse and Aalborg handball clubs as cases