A co-evolutionary model combined mixed-strategy and network adaptation by severing disassortative neighbors promotes cooperation in prisoner’s dilemma games

2021 ◽  
Vol 143 ◽  
pp. 110603
Author(s):  
Kohei Miyaji ◽  
Jun Tanimoto
Games ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 100 ◽  
Author(s):  
Shun Kurokawa ◽  
Joe Yuichiro Wakano ◽  
Yasuo Ihara

Evolution of cooperation by reciprocity has been studied using two-player and n-player repeated prisoner’s dilemma games. An interesting feature specific to the n-player case is that players can vary in generosity, or how many defections they tolerate in a given round of a repeated game. Reciprocators are quicker to detect defectors to withdraw further cooperation when less generous, and better at maintaining a long-term cooperation in the presence of rare defectors when more generous. A previous analysis on a stochastic evolutionary model of the n-player repeated prisoner’s dilemma has shown that the fixation probability of a single reciprocator in a population of defectors can be maximized for a moderate level of generosity. However, the analysis is limited in that it considers only tit-for-tat-type reciprocators within the conventional linear payoff assumption. Here we extend the previous study by removing these limitations and show that, if the games are repeated sufficiently many times, considering non-tit-for-tat type strategies does not alter the previous results, while the introduction of non-linear payoffs sometimes does. In particular, under certain conditions, the fixation probability is maximized for a “paradoxical” strategy, which cooperates in the presence of fewer cooperating opponents than in other situations in which it defects.


2019 ◽  
Vol 6 (7) ◽  
pp. 182142
Author(s):  
Leonie Heuer ◽  
Andreas Orland

Cooperation is—despite not being predicted by game theory—a widely documented aspect of human behaviour in Prisoner’s Dilemma (PD) situations. This article presents a comparison between subjects restricted to playing pure strategies and subjects allowed to play mixed strategies in a one-shot symmetric PD laboratory experiment. Subjects interact with 10 other subjects and take their decisions all at once. Because subjects in the mixed-strategy treatment group are allowed to condition their level of cooperation more precisely on their beliefs about their counterparts’ level of cooperation, we predicted the cooperation rate in the mixed-strategy treatment group to be higher than in the pure-strategy control group. The results of our experiment reject our prediction: even after controlling for beliefs about the other subjects’ level of cooperation, we find that cooperation in the mixed-strategy group is lower than in the pure-strategy group. We also find, however, that subjects in the mixed-strategy group condition their cooperative behaviour more closely on their beliefs than in the pure-strategy group. In the mixed-strategy group, most subjects choose intermediate levels of cooperation.


2011 ◽  
Vol 22 (04) ◽  
pp. 401-417 ◽  
Author(s):  
JUN TANIMOTO

We present and numerically investigate a quadruple co-evolutionary model for 2 × 2 Prisoner's Dilemma games which allows not only for agents to adopt strategy (Cooperation C or Defection D) and for network topology, but also for the probability of link rewiring that controls the speed of network evolution and the updating rule itself. The results of a series of simulations reveal that C agents in a coexisting phase increase their rewiring probability to avoid neighboring D agents' exploitation through the Game Exit Option. This evolutionary process leads most agents to adopt pairwise updating even though Imitation Max update adopted by all agents brings a higher payoff.


2020 ◽  
Vol 31 (06) ◽  
pp. 2050077
Author(s):  
Hai Zhu ◽  
Zhen Wang ◽  
Qingyang Zhao ◽  
Xing Jin ◽  
Lanping Yu

Due to the heterogeneity of strategy updating rules progressively destroying the cluster of cooperators, cooperation would be heavily suppressed when players adopt mixed strategy updating rules. Thus, how to improve the emergence of cooperation with the scenario of heterogeneous strategy updating rules becomes an important open issue. In this paper, we introduce the memory factor into the game model, and then study the joint effect of memory and heterogeneous strategy updating rules on the emergence of cooperation. Detailly, in our game model, memory-based imitation and innovation are chosen as two different strategy updating rules. Afterwards, the annealing and quenching rules are specifically used as the methods to mix the proposed two memory-based strategy updating rules. At last, Monte Carlo simulations are conducted to demonstrate the significance of our model. The simulation results show that for memory-based imitators, memory is not always effective in promoting cooperation. It’s more like a catalyst. When the proportion of the memory-based imitation is large, it promotes the emergence of cooperation. When the proportion of innovation is large, it accelerates the extinction of cooperation; for overall proportion of cooperation, memory effectively promotes the emergence of cooperation and improves the ability of cooperators to resist high temptation, but memory is a partial optimization, it cannot offset the deterioration of cooperation caused by heterogeneous strategies updating rules, memory only reduces the degree of deterioration. Finally, compared with the annealing rule, the change of quenching rule is more smooth, because it is easier for cooperators to form clusters under the quenching rule. Our investigation sheds some light to the role of memory in prisoner’s dilemma game under heterogeneous strategies updating rules.


2014 ◽  
Vol 17 (02) ◽  
pp. 1450011 ◽  
Author(s):  
SIMONE RIGHI ◽  
KÁROLY TAKÁCS

The evolution of unconditional cooperation is one of the fundamental problems in science. A new solution is proposed to solve this puzzle. We treat this issue with an evolutionary model in which agents play the Prisoner's Dilemma on signed networks. The topology is allowed to co-evolve with relational signs as well as with agent strategies. We introduce a strategy that is conditional on the emotional content embedded in network signs. We show that this strategy acts as a catalyst and creates favorable conditions for the spread of unconditional cooperation. In line with the literature, we found evidence that the evolution of cooperation most likely occurs in networks with relatively high chances of rewiring and with low likelihood of strategy adoption. While a low likelihood of rewiring enhances cooperation, a very high likelihood seems to limit its diffusion. Furthermore, unlike in nonsigned networks, cooperation becomes more prevalent in denser topologies.


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