## 5 Simulation Model with Human Behavior
### Verification of the Model  
To verify the described model, the results of the simulation were compared with the results of the experiment. The simulation was executed 1000 times with the same initial settings as used in the experiment (27 agents, \(t_{game}=90\) min, \(f_{BC}=10\) s, \(d=0.87\), \(t_{initial}=300\) s, \(t_{limit}=20\) s). The results of the simulations were compared with the experiment based on four variables: the transaction fee of the confirmed transactions, the price of the provided services, the number of services on the market, and the frequency of the provided services in time. For each variable, the obtained simulation results were observed to see whether they followed the normal distribution; if they passed this test, they are presented using the average value and the standard deviation. The normality test was performed using the Kolmogorov-Smirnov (KS) test for normality, which rejects the normality hypothesis if the \(p\) value is less than 0.05. Figure 12 presents a comparison of the transaction fee for confirmed transactions over time between the experimental results and the results of the simulations. The KS normality test confirmed the zero hypothesis (\(p=0.11\)). There is a noticeable difference in the first quarter of the game, when the transaction fee in the simulation is much smaller than it was in the experiment. This deviation at the beginning of the game is due to multiple reasons, such as the learning process of the players in the real experiment, hesitation, and waiting for the strategic moves of other players. The agents in the simulation, on the other hand, follow preprogrammed decision-making strategies from the beginning. In the rest of the game, however, the simulation model better describes the behavior of the players in the real experiment, as the value of the transaction fee in the experiment is within the standard deviation of the transaction fee in the simulations. Figure 13 shows a comparison of the average price between the results of the experiment and the simulations for all three types of provided services. The simulation results again follow a normal distribution (Service A: \(p=0.59\), Service B: \(p=0.67\), Service C: \(p=0.56\)). In the case of this characteristic, the simulation model describes the behavior of the players well throughout the game, as the obtained results of the experiment almost overlap with the average values (dark-colored lines) in the simulation. The average price values of the three types of services deviate less from each other over time in the case of the simulation compared to the experiment, though the values from the experiment are within the standard deviation of the simulation results (brightly colored area). Figure 14 presents a comparison of the results of the experiment and the simulations for the number of services on the market. The simulation results confirm the hypothesis of normality (\(p=0.69\)). Again, there is a noticeable difference between the results of the experiment and the simulations in the first quarter of the game. In the case of the simulations, agents buy services on the market much faster than players did in the experiment. This might be because agents have more funds in their accounts due to the lower transaction costs in the first quarter of the game, as described above, and might consequently purchase more services. Noisy changes in the average value and standard deviation occur with this variable, which may be a consequence of the number of offers fluctuating on the market in each simulation being slightly offset in time. As a result, the simulation model does not describe this fluctuation of the market supply perfectly, and only describes the tendency of the change in the value of the characteristic. Figure 12: Comparison of transaction fee between experimental and simulation results. Figure 13: Comparison of service price between the experimental and simulation results. Figure 15 shows a comparison of the results of the experiment and simulations for the frequency of service provision over time.