# -- Select and Attempt task -- ```
## 4 Enhancing Performance by Avoiding Unwarranted Task Executions
### The Proposed CA Algorithm for the Early Detection of Bad Providers
The results are depicted in Figure 2. Figure 2a demonstrates that CA_NEW consistently outperforms CA_OLD in all interactions, with an average difference of 2 UG units. Figure 2b shows that CA_NEW performs better than FIRE in all interactions except the first one. ### The Performance of the New CA Algorithm in the Static Setting

This subsection presents the results of Experiment 3, which evaluates the performance of the updated CA algorithm (CA_NEW) in a static environment without any dynamic factors. The findings are depicted in Figure 3. Figure 3a demonstrates that CA_NEW performs better than CA_OLD in the initial interactions. Figure 3b shows that CA_NEW surpasses FIRE in all interactions, except for the first one. Figure 2: (**a**) A performance comparison of CA_NEW and CA_OLD when providers switch performance profiles with 2% probability per round: CA_NEW consistently outperforms CA_OLD by an average of 2 UG units. (**b**) A performance comparison of CA_NEW and FIRE when providers switch performance profiles with 2% probability per round: CA_NEW outperforms FIRE in all interactions except for the first one. **Experiment 7**. The provider population changes at a maximum of 20% in every round (\(p_{PPC}=0.20\)). The results are shown in Figure 7.

**Experiment 8**. The provider population changes at a maximum of 30% in every round (\(p_{PPC}=0.30\)). The results are shown in Figure 8.

In Experiments 4-6, we compare the performance of CA_NEW to both CA_OLD and FIRE. Figures 4a, 5a and 6a show that CA_NEW significantly outperforms CA_OLD, achieving higher UG across all interactions. Figures 4b, 5b and 6b reveal that as the provider population change rate rises from 2% to 10%, CA_NEW maintains better performance than FIRE. Figure 9a,b demonstrate that CA_NEW is more resilient than CA_OLD to changes in provider population. Specifically, when the provider population change rate increases from 2% to 10%, CA_OLD's performance drops by 4 UG units (Figure 9a), whereas CA_NEW's performance drops only 2 UG units (Figure 9b). Figure 5: (**a**) A performance comparison of CA_NEW and CA_OLD when the provider population changes with 5% probability per round: CA_NEW outperforms in all interactions. (**b**) A performance comparison of CA_NEW and FIRE when the provider population changes with 5% probability per round. Figure 1:0 (**a**) A performance comparison of CA_NEW and CA_OLD when the provider population changes with 10% probability per round: CA_NEW outperforms in all interactions. (**b**) A performance comparison of CA_NEW and FIRE when the provider population changes with 10% probability per round. Figure 9b,c indicate that CA_NEW's performance drops more sharply than FIRE's, suggesting that FIRE is more resilient to this environmental change. This trend raises the expectation that FIRE will eventually surpass CA_NEW at a higher provider population change rate. To verify this hypothesis, we conducted Experiments 7 and 8. The results, shown in Figures 7 and 8, confirm that when the provider population change rate reaches 30%, FIRE outperforms CA_NEW. As discussed in Section 4.2 of our previous work [7], FIRE demonstrates greater resilience to changes in the provider population compared to CA. This is primarily due to FIRE's continuous adaptation over time, which enables it to maintain or even improve its performance. In these experiments, consumers rely on witness reputation, which gradually increases as witnesses (other consumers) remain in the system, contributing to FIRE's stability. In contrast, CA heavily depends on the provider's knowledge of their capabilities, and when the provider population changes, newcomers must learn from scratch, leading to a more significant decline in performance. While CA_NEW shows an improvement over CA_OLD in scenarios involving provider population change, the fundamental differences in the underlying mechanisms still allow FIRE to outperform CA_NEW under these conditions.