Understand the game model of public goods, the evolution and dissemination of cooperation, and the impact of rewards and punishments on cooperation evolution under random networks, and use Monte Carlo simulation analysis to achieve mechanism modeling.
There are many restaurants of all sizes in the city, and each restaurant has a probability of being subjected to hygiene checks by relevant departments every day. If hygiene is not done on that day (i.e. betrayal), fines will be imposed. Use this mechanism to demonstrate cooperation and betrayal on four networks.
When an individual is a collaborator and regardless of whether they undergo inspection or not, the collaborator has already done a good job of hygiene and will not be punished. At this point, the profit that the individual collaborator obtains from the whole is as follows:
When an individual is a betrayer and the probability of being tested meets the following criteria.
The betrayer has not yet done a good job in hygiene, and at this point, the benefits of the betrayer are:
Rewards are awarded when the group cooperation rate is less than 0.5. Finally, calculate the total income of the individual:
Plus benefits from other groups
Parameter Description
c: Cooperation costs for collaborators
r: Input-output ratio
k: Rationality level
penaltyAmount:Fine
rewardAmount: Reward
reward: group reward
Cooperation_rate: Group combination work rate
M1: Number of rows
M2: Number of columns
N: Number of game rounds
A: Denotes a collaborator or betrayer
D: Benefits of each individual in the group
E: Total income per individual
tongji: stores the proportion of collaborators at each moment
NC: represents the number of co authors in group i
NCD：Number of individuals in group i
totalpay：Represented as the total return of individual i playing games in multiple groups
individualRewards：All rewards received by individuals
| diffNetwork default | penaltyAmount | rewardAmount |
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