# -- Select and Attempt task -- ```
## 4 Enhancing Performance by Avoiding Unwarranted Task Executions
### The Proposed CA Algorithm for the Early Detection of Bad Providers
Figure 1:1 A performance comparison of CA_NEW and FIRE when the provider population changes with 30% probability per round. Figure 1:2 A performance comparison of CA_NEW and FIRE when the provider population changes with 20% probability per round. ### The Performance of the New CA Algorithm in Consumer Population Changes

This section evaluates the performance of the updated CA algorithm (CA_NEW) in comparison to both CA_OLD and FIRE under conditions where the consumer population gradually fluctuates by up to 10%, through a series of three experiments. **Experiment 9**. The consumer population changes at a maximum of 2% in every round (\(p_{CPC}=0.02\)). The results are shown in Figure 1:3

**Experiment 10**. The consumer population changes at a maximum of 5% in every round (\(p_{CPC}=0.05\)). The results are shown in Figure 1:4

**Experiment 11**. The consumer population changes at a maximum of 10% in every round (\(p_{CPC}=0.10\)). The results are shown in Figure 1:5

Figures 9a, 10a and 11a illustrate that CA_NEW outperforms CA_OLD, generally achieving a higher UG in the initial interactions. Figures 9b, 10b and 11b demonstrate that CA_NEW consistently performs better than FIRE throughout all interactions in this environmental change. Figure 1:6 (**a**) Performance comparison of CA_OLD when provider population changes with probability of 2%, 5%, and 10%; performance drops by 4 UG units. (**b**) Performance comparison of CA_NEW when provider population changes with probability of 2%, 5%, and 10%; performance drops by 2 UG units. (**c**) Performance comparison of FIRE when provider population changes with probability of 2%, 5%, and 10%; FIRE is more resilient than CA to this environmental change. Figure 1:7 (**a**) Performance comparison of CA_NEW and CA_OLD when consumer population changes with probability of 5%. (**b**) Performance comparison of CA_NEW and FIRE when consumer population changes with probability of 5%. Figure 1:8 (**a**) Performance comparison of CA_NEW and CA_OLD when consumer population changes with probability of 10%. (**b**) Performance comparison of CA_NEW and FIRE when consumer population changes with probability of 10%. Figure 1:9 (**a**) Performance comparison of CA_NEW and CA_OLD when consumer population changes with probability of 2%. (**b**) Performance comparison of CA_NEW and FIRE when consumer population changes with probability of 2%. Figure 13a,b show that in the first interactions, both CA_OLD and CA_NEW improve their performance as the consumer population change rate increases from 2% to 10%. Nevertheless, Figure 12a reveals that when CPC = 10%, CA_OLD slightly surpasses CA_NEW in the first interaction. A possible explanation for this is that when CPC = 10%, the average UG of the first interaction is influenced by a larger number of newcomer agents who have their first interaction in later simulation rounds. During these rounds, service providers have established more connections and can more accurately evaluate their ability to provide the service using CA_OLD, resulting in a higher UG for service consumers. This observation led us to hypothesize that CA_OLD, compared to CA_NEW, is a more suitable choice for service providers that have remained in the system longer and have gained more knowledge about their service-providing capabilities, assuming their capabilities remain unchanged over time. ### The Performance of the New CA Algorithm in Consumer and Provider Location Changes

In this subsection, we evaluate the performance of the updated CA algorithm (CA_NEW) in comparison to both CA_OLD and FIRE under conditions where consumers and providers change locations, by conducting the following two experiments. **Experiment 12**. A consumer may move to a new location on the spherical world at a maximum angular distance of \(\pi/20\) with a probability of 0.10 in every round (P\({}_{\text{CLC}}~{}=~{}0.10,\Delta\Phi=\pi/20\)).