Tallis Training

Recommendation Rules

When a decision is enacted, the Tallis Engine determines the effect of each argument and in turn the net support for a given candidate. The recommendation rule is then used to determine whether or not a particular candidate is recommended.

Defining a Recommendation Rule

To define a recommendation rule for a candidate, select the Decide tab.

Select the candidate for which you want to define a recommendation rule from the drop-down box.

The Rule field defines an expression that must be true for the candidate to be recommended. It is pre-populated with a default expression:

netsupport(CurrentDecision, CurrentCandidate) >= 1

The default rule states that for the candidate to be recommended, its aggregated support (or “netsupport”) has to be greater than or equal to 1.

Recommendation rules are typically based on the netsupport of the candidate; but any truth-valued expression can serve as a recommendation rule. Recommendation rules can also be based on the netsupport of a competing candidate. For example, in a Referral decision which has two candidates, Refer and Do not refer, the recommendation rule of the Do not refer candidate might be:

netsupport(ReferralDecision, ReferCandidate) < 1

This rule means that the Do not refer candidate will only be recommended if the Refer candidate’s netsupport is less than 1. Note that this rule ignores the netsupport of the Do not refer candidate itself.

Note: Selecting Unlocked in the Rule Input Mode field will reset the recommendation to the default rule.

See Also

  • Decisions: Creating a decision based on results of an enquiry
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