Inertia of Social Rotation in Laboratory 2×2 Population Games

2012 ◽  
Author(s):  
Bin Xu ◽  
Zhijian Wang
Keyword(s):  
Population Games

scholarly journals Boltzmann Distributed Replicator Dynamics: Population Games in a Microgrid Context

Games ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 8
Author(s):  
Gustavo Chica-Pedraza ◽  
Eduardo Mojica-Nava ◽  
Ernesto Cadena-Muñoz
Keyword(s):  
Control Method ◽  
Optimization Problems ◽  
Replicator Dynamics ◽  
Boltzmann Distribution ◽  
Full Information ◽  
Multi Agent Systems ◽  
Q Learning ◽  
Population Games ◽  
Distributed Approach ◽  
Multi Agent

Multi-Agent Systems (MAS) have been used to solve several optimization problems in control systems. MAS allow understanding the interactions between agents and the complexity of the system, thus generating functional models that are closer to reality. However, these approaches assume that information between agents is always available, which means the employment of a full-information model. Some tendencies have been growing in importance to tackle scenarios where information constraints are relevant issues. In this sense, game theory approaches appear as a useful technique that use a strategy concept to analyze the interactions of the agents and achieve the maximization of agent outcomes. In this paper, we propose a distributed control method of learning that allows analyzing the effect of the exploration concept in MAS. The dynamics obtained use Q-learning from reinforcement learning as a way to include the concept of exploration into the classic exploration-less Replicator Dynamics equation. Then, the Boltzmann distribution is used to introduce the Boltzmann-Based Distributed Replicator Dynamics as a tool for controlling agents behaviors. This distributed approach can be used in several engineering applications, where communications constraints between agents are considered. The behavior of the proposed method is analyzed using a smart grid application for validation purposes. Results show that despite the lack of full information of the system, by controlling some parameters of the method, it has similar behavior to the traditional centralized approaches.

scholarly journals Endogenous Networks in Random Population Games

2003 ◽  
Author(s):  
Giorgio Fagiolo ◽  
Luigi Marengo ◽  
Marco Valente
Keyword(s):  
Population Games ◽  
Endogenous Networks

scholarly journals DIVERSITY AND ADAPTATION IN LARGE POPULATION GAMES

2004 ◽  
Vol 18 (17n19) ◽  
pp. 2422-2431 ◽  
Author(s):  
K. Y. MICHAEL WONG ◽  
S. W. LIM ◽  
PEIXUN LUO
Keyword(s):  
Steady State ◽  
Large Population ◽  
Transient State ◽  
Maladaptive Behavior ◽  
Uneven Distribution ◽  
System Efficiency ◽  
Population Games ◽  
Distribution Of Resources

We consider a version of large population games whose players compete for resources using strategies with adaptable preferences. The system efficiency is measured by the variance of the decisions. In the regime where the system can be plagued by the maladaptive behavior of the players, we find that diversity among the players improves the system efficiency, though it slows the convergence to the steady state. Diversity causes a mild spread of resources at the transient state, but reduces the uneven distribution of resources in the steady state.

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