In an ultimatum game where competitive pressures and alternating roles exist, we suppose that players make their decisions based on the net profit of their own. Here we conduct a behavioral experiment in a selection examination, and then we establish a model and study the evolution of strategies...

In our previous study [Zhu et al., Quantum game interpretation for a special case of Parrondo’s paradox, Physica A 390 (2011) 579], the capital-dependent Parrondo’s game where one game depends on the capital modulus M=4 was shown not to have a definite stationary probability distribution and...

For the multi-agent spatial Parrondo’s games, the available theoretical analysis methods based on the discrete-time Markov chain were assumed that the losing and winning states of an ensemble of N players were represented to be the system states. The number of system states was 2N types....

A multi-agent Parrondo’s model is proposed in the paper. The model includes link A based on the rewiring mechanism (the network evolution) + game B (dependent on the spatial neighbors). Moreover, to produce the paradoxical effect and analyze the “agitating” effect of the network...

Based on the original Parrondo’s game and on the case where game A and game B are played randomly with modulo M=4, the processes of the game are divided into odd and even numbered plays, where the probability of playing game A in odd numbers is γ1 and the probability of playing game A in even...

By using the discrete Markov chain method, Parrondo’s paradox is studied by means of theoretical analysis and computer simulation, built on the case of game AB played in alternation with modulus M=4. We find that such a case does not have a definite stationary probability distribution and that...

Most existing methods for detection of community overlap cannot balance efficiency and accuracy for large and densely overlapping networks. To quickly identify overlapping communities for such networks, we propose a new method that uses belief propagation and conflict (PCB) to occupy...