From OpenCog

The Procedure Evaluation Process

Now we give a more thorough treatment of the procedure evaluation process, as embodied in the effort-based or adaptive-evaluation-order evaluators discussed above. The process of procedure evaluation is somewhat complex, because it encompasses three interdependent processes:

  • The mechanics of procedure evaluation, which in the OCP design involves traversing Combo trees in an appropriate order. When a Combo tree node referring to a predicate or schema is encountered during Combo tree traversal, the process of predicate evaluation or schema execution must be invoked.
  • The evaluation of the truth values of predicates — which involves a combination of inference and (in the case of grounded predicates) procedure evaluation.
  • The computation of the truth values of schemata — which may involve inference as well as procedure evaluation.

We now review each of these processes.

Truth Value Evaluation

What happens when the procedure evaluation process encounters a Combo tree Node that represents a predicate or compound term? The same thing as when some other OCP process decides it wants to evaluate the truth value of a PredicateNode or CompoundTermNode: the generic process of predicate evaluation is initiated.

This process is carried out by a TruthValueEvaluator object. There are several varieties of TruthValueEvaluator, which fall into the following hierarchy:

   DirectTruthValueEvaluator (abstract)
   InferentialTruthValueEvaluator (abstract)

A DirectTruthValueEvaluator evaluates a grounded predicate by directly executing it on one or more inputs; an InferentialTruthValueEvaluator evaluates via inference based on the previously recorded, or specifically elicited, behaviors of other related predicates or compound terms. A MixedTruthValueEvaluator contains references to a DirectTruthValueEvaluator and an InferentialTruthValueEvaluator, and contains a weight that tells it how to balance the outputs from the two.

Direct truth value evaluation has two cases. In one case, there is a given argument for the predicate; then, one simply plugs this argument in to the predicate's internal Combo tree, and passes the problem off to an appropriately selected ProcedureEvaluator. In the other case, there is no given argument, and one is looking for the truth value of the predicate in general. In this latter case, some estimation is required. It is not plausible to evaluate the truth value of a predicate on every possible argument, so one must sample a bunch of arguments and then record the resulting probability distribution. A greater or fewer number of samples may be taken, based on the amount of effort that's been allocated to the evaluation process. It's also possible to evaluate the truth value of a predicate in a given context (information that's recorded via embedding in a ContextLink); in this case, the random sampling is restricted to inputs that lie within the specified context.

On the other hand, the job of an InferentialTruthValueEvaluator is to use inference rather than direct evaluation to guess the truth value of a predicate (sometimes on a particular argument, sometimes in general). There are several different control strategies that may be applied here, depending on the amount of effort allocated. The simplest strategy is to rely on analogy, simply searching for similar predicates and using their truth values as guidance. (In the case where a specific argument is given, one searches for similar predicates that have been evaluated on similar arguments.) If more effort is available, then a more sophisticated strategy may be taken. Generally, an InferentialTruthValueEvaluator may invoke a SchemaNode that embodies an inference control strategy for guiding the truth value estimation process. These SchemaNodes may then be learned like any others.

Finally, a MixedTruthValueEvaluator operates by consulting a DirectTruthValueEvaluator and/or an InferentialTruthValueEvaluator as necessary, and merging the results. Specifically, in the case of an ungrounded PredicateNode, it simply returns the output of the InferentialTruthValueEvaluator it has chosen. But in the case of a GroundedPredicateNode, it returns a weighted average of the directly evaluated and inferred values, where the weight is a parameter. In general, this weighting may be done by a SchemaNode that is selected by the MixedTruthValueEvaluator; and these schemata may be adaptively learned.

Schema Execution

Finally, schema execution is handled similarly to truth value evaluation, but it's a bit simpler in the details. Schemata have their outputs evaluated by SchemaExecutor objects, which in turn invoke ProcedureEvaluator objects. We have the hierarchy:

   DirectSchemaExecutor (abstract)
   InferentialSchemaExecutor (abstract)

A DirectSchemaExecutor evaluates the output of a schema by directly executing it on some inputs; an InferentialSchemaExecutor evaluates via inference based on the previously recorded, or specifically elicited, behaviors of other related schemata. A MixedSchemaExecutor contains references to a DirectSchemaExecutor and an InferentialSchemaExecutor, and contains a weight that tells it how to balance the outputs from the two (not always obvious, depending on the output type in question).

Contexts may be used in schema execution, but they're used only indirectly, via being passed to TruthValueEvaluators used for evaluating truth values of PredicateNodes or CompoundTermNodes that occur internally in schemata being executed.