scholarly journals Consensus towards Partially Cooperative Strategies in Self-regulated Evolutionary Games on Networks

2021 ◽  
Author(s):  
Dario Madeo ◽  
Chiara Mocenni
Keyword(s):  
Mixed Strategy ◽  
Cooperative Behavior ◽  
Evolutionary Games ◽  
Asymptotically Stable ◽  
Stag Hunt ◽  
Balanced Development ◽  
Cooperative Strategies ◽  
Mixed Strategy Nash Equilibrium ◽  
Emergence Of Cooperation ◽  
Globally Stable

Cooperation is widely recognized to be challenging for the well-balanced development of human societies. The emergence of cooperation in populations has been largely studied in the context of the Prisoner's Dilemma game, where temptation to defect and fear to be betrayed by others often activate defective strategies. In this paper we analyze the decision making mechanisms fostering cooperation in the two-strategy Stag-Hunt and Chicken games, which include the mixed strategy Nash equilibrium, describing partially cooperative behavior. We find the conditions for which cooperation is asymptotically stable in both full and partial cases, and we show that the partially cooperative steady state is also globally stable in the simplex. Furthermore, we show that the last can be more rewarding than the first, thus making the mixed strategy effective, although people cooperate at a lower level with respect to the maximum allowed, as it is reasonably expected in real situations. Our findings highlight the importance of Stag-Hunt and Chicken games in understanding the emergence of cooperation in social networks.

scholarly journals Consensus towards Partially Cooperative Strategies in Self-Regulated Evolutionary Games on Networks

Games ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 60
Author(s):  
Dario Madeo ◽  
Chiara Mocenni
Keyword(s):  
Prisoner's Dilemma ◽  
Prisoner’S Dilemma ◽  
Evolutionary Games ◽  
Prisoner’S Dilemma Game ◽  
Stag Hunt ◽  
Balanced Development ◽  
Cooperative Strategies ◽  
Partial Cooperation ◽  
Stag Hunt Game ◽  
Prisoner's Dilemma Game

Cooperation is widely recognized to be fundamental for the well-balanced development of human societies. Several different approaches have been proposed to explain the emergence of cooperation in populations of individuals playing the Prisoner’s Dilemma game, characterized by two concurrent natural mechanisms: the temptation to defect and the fear to be betrayed by others. Few results are available for analyzing situations where only the temptation to defect (Chicken game) or the fear to be betrayed (Stag-Hunt game) is present. In this paper, we analyze the emergence of full and partial cooperation for these classes of games. We find the conditions for which these Nash equilibria are asymptotically stable, and we show that the partial one is also globally stable. Furthermore, in the Chicken and Stag-Hunt games, partial cooperation has been found to be more rewarding than the full one of the Prisoner’s Dilemma game. This result highlights the importance of such games for understanding and sustaining different levels of cooperation in social networks.

The analysis of evolutionary prisoner’s dilemma game based on weighting effect

2021 ◽  
pp. 2150066
Author(s):  
Xinting Hu ◽  
Mengyun Wu
Keyword(s):  
Prisoner's Dilemma ◽  
Weighting Function ◽  
Random Network ◽  
Cooperative Behavior ◽  
Equilibrium Points ◽  
Prisoner’S Dilemma ◽  
The Real ◽  
Scale Free ◽  
Cooperative Strategies ◽  
Average Payoff

In this paper, an improved evolutionary prisoner’s dilemma (PD) game model is proposed by considering the weighting effect. Taking into account individual’s perceived payoff (benefits), the evolutionary tendency of the cooperators and three equilibrium points of the proposed model are obtained. We then numerically investigate how different exterior and interior factors influence on individuals’ cooperative behavior and their payoff both in the ER random network and the BA scale-free network. Our results reveal that the heterogeneous network structure is conducive to cooperation. In addition, the existence of leader nodes is an important driving force for promoting individuals’ cooperation. By further analyzing the rationality coefficient which appears in the weighting function, we obtain that a greater of irrationality could lead more people to take cooperative strategies. Finally, two indicators which are used to measure the real average payoff and perceived average payoff are defined. The results show that the real average payoff and perceived average payoff are larger in the heterogeneity network than that in homogeneous network.

scholarly journals PHASE TRANSITION IN EVOLUTIONARY GAMES

1999 ◽  
Vol 14 (10) ◽  
pp. 1551-1559 ◽  
Author(s):  
ZHEN CAO ◽  
RUDOLPH C. HWA
Keyword(s):  
Phase Transition ◽  
Critical Region ◽  
Nuclear Physics ◽  
Cooperative Behavior ◽  
Evolutionary Games ◽  
Scaling Exponent ◽  
Factorial Moments ◽  
Physical Systems ◽  
Prisoners Dilemma ◽  
Evolution Dynamics

The evolution of cooperative behavior is studied in the deterministic version of the Prisoners' Dilemma on a two-dimensional lattice. The payoff parameter is set at the critical region 1.8<b<2.0, where clusters of cooperators are formed in all spatial sizes. Using the factorial moments developed in particle and nuclear physics for the study of phase transition, the distribution of cooperators is studied as a function of the bin size covering varying numbers of lattice cells. From the scaling behavior of the moments a scaling exponent is determined and is found to lie in the range where phase transitions are known to take place in physical systems. It is therefore inferred that when the payoff parameter is increased through the critical region the biological system of cooperators undergoes a phase transition to defectors. The universality of the critical behavior is thus extended to include also this particular model of evolution dynamics.

scholarly journals Multi-objective Optimization of Accommodation Capacity for Distributed Generation Based on Mixed Strategy Nash Equilibrium, Considering Distribution Network Flexibility

2019 ◽  
Vol 9 (20) ◽  
pp. 4395 ◽  
Author(s):  
Weisheng Liu ◽  
Jian Wu ◽  
Fei Wang ◽  
Yixin Huang ◽  
Qiongdan Dai ◽  
...  
Keyword(s):  
Nash Equilibrium ◽  
Distributed Generation ◽  
Mixed Strategy ◽  
Distribution Network ◽  
Distribution Networks ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Mixed Strategy Nash Equilibrium ◽  
Network Flexibility ◽  
Strategy Nash Equilibrium

The increasing penetration of distributed generation (DG) brings about great fluctuation and uncertainty in distribution networks. In order to improve the ability of distribution networks to cope with disturbances caused by uncertainties and to evaluate the maximum accommodation capacity of DG, a multi-objective programming method for evaluation of the accommodation capacity of distribution networks for DG is proposed, considering the flexibility of distribution networks in this paper. Firstly, a multi-objective optimization model for determining the maximum accommodation of DG by considering the flexibility of distribution networks is constructed, aiming at maximizing the daily energy consumption, minimizing the voltage amplitude deviation, and maximizing the line capacity margin. Secondly, the comprehensive learning particle swarm optimization (CLPSO) algorithm is used to solve the multi-objective optimization model. Then, the mixed strategy Nash equilibrium is introduced to obtain the frontier solution with the optimal joint equilibrium value in the Pareto solution set. Finally, the effectiveness of the proposed method is demonstrated with an actual distribution network in China. The simulation results show that the proposed planning method can effectively find the Pareto optimal solution set by considering multiple objectives, and can obtain the optimal equilibrium solution for DG accommodation capacity and distribution network flexibility.

Cooperative Strategies and Genome Cybernetics in Formation of Complex Bacterial Patterns

1994 ◽  
Vol 367 ◽  
Author(s):  
Eshel Ben-Jacob ◽  
Ofer Shochet ◽  
Inon Cohen ◽  
Adam Tenenbaum ◽  
Andras CzirÓk ◽  
...  
Keyword(s):  
Pattern Formation ◽  
Degrees Of Freedom ◽  
Cooperative Behavior ◽  
Building Blocks ◽  
Growth Conditions ◽  
Living Systems ◽  
Cooperative Strategies ◽  
Additional Level ◽  
Bacterial Patterns ◽  
The Individual

AbstractWe present a study of interfacial pattern formation during growth of bacterial colonies. Growth of bacterial colonies bears similarities but presents an inherent additional level of complexity in comparison with non-living systems. In the former case, the building blocks themselves are living systems, each with its own autonomous self-interest and internal degrees of freedom. The bacteria have developed sophisticated communication channels, which they utilize when growth conditions are tough. Here we present a non-local communicating walkers model to study the effect of local bacterium-bacterium interaction and communication via chemotaxis signaling. We demonstrate how communication enables the colony to develop complex patterns in response to adverse growth conditions. This self-organization of the colony, which can be achieved only via cooperative behavior of the bacteria, may be viewed as the outcome of an interplay between the micro-level (the individual bacterium) and the macro-level (the colony). Some qualitative features of the complex morphologies can be accounted for by invoking ideas from pattern formation in non-living systems together with a simplified model of chemotactic “feedback”.

Researches on Data Correctness and Completeness in Cloud Computing Based on Game Theory

2014 ◽  
Vol 496-500 ◽  
pp. 2069-2072
Author(s):  
Yong Hong Yu ◽  
Li Wu
Keyword(s):  
Game Theory ◽  
Cloud Computing ◽  
Data Security ◽  
Mixed Strategy ◽  
Complete Information ◽  
Security Technologies ◽  
Mixed Strategy Nash Equilibrium ◽  
Countermeasures And Suggestions ◽  
Trusted Data ◽  
Database Service

Ensuring data correctness and data completeness in cloud computing, in addition to security technologies, many other factors need also be considered, such as the behaviors of participants of cloud computing. This paper discusses the data correctness and completeness in cloud computing based on the perspective of game theory. It built a complete information static game theory frame between a trusted data center and an un-trusted database service provider, and gave the mixed strategy Nash equilibrium. It also proposed some countermeasures and suggestions to improve the data security in cloud computing.

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