Analyzing the relationship between the feature "other_payment_plans" and the task of determining whether a person receives credit, we can make some assumptions based on prior knowledge:
- If a person has no other installment plans (other_payment_plans = 'none'), it is likely that they will receive credit.
- If a person has an installment plan with a bank (other_payment_plans = 'bank'), it is possible that they will receive credit.
- If a person has an installment plan with a store (other_payment_plans = 'stores'), it is less likely that they will receive credit.

Based on these assumptions, we can create a dictionary as follows:

```json
{
	"yes": ["none", "bank"],
	"no": ["stores"]
}
```

Note that we include the possible values of the feature for each target class, considering the assumptions made. The values included in the dictionary are not an exhaustive list of all possible values, but just the ones that seem relevant based on the relationship analysis.