The concept of a truth value comes from the discipline of cognitive science which is basically the science of how we know what we know. In cognitive science the concepts of proposition and truth value are directly related. A proposition is considered to be the smallest unit of thought that can be assigned a measure of truth (ref). NetWeaver knowledge bases are based on propositional logic and every NetWeaver network asserts some proposition concerning the topic it is constructed to evaluate. The key attribute, or state variable, of a network is its truth value which expresses the degree to which antecedent information supports or contradicts the proposition that the network is designed to test.

If all evidence antecedent to a proposition supports the assertion, then the truth value for the network is 1 (completely true). If all evidence antecedent to an assertion is contrary to that assertion, then the truth value for the network is -1 (completely false). If there is no evidence for or against the assertion, then the truth value is 0 (undetermined). Truth values also may be partially true or partially false. Three conditions give rise to this condition in NetWeaver:

1. Some of the data needed to fully evaluate the node or dependency network has not yet been supplied when an evaluation of a network is being performed.
2. The data are missing and cannot be supplied.
3. One or more of the data items that influence the truth value of a dependency network have been evaluated against a fuzzy argument and found not to have full membership in the fuzzy set defined by the fuzzy argument.

As a noun, the term antecedent literally means “something that comes before something else.” An antecedent network, for example, is a network that another network depends upon for its truth value. The term antecedent (the adjective is antecedent) is equally applicable to dependency networks, relational nodes, and data links. An antecedent network, node, or data link logically precedes its dependent network or node in the sense that the value of the antecedent must be known in order to evaluate a network or node that depends on it.

Although the networks of hierarchies in a NetWeaver knowledge base are more general relational structures than simple hierarchies, there are some restrictions on the structure of knowledge bases because they are based on propositional logic. In particular, the NetWeaver inference engine monitors the construction of knowledge bases, and will not allow a dependency structure that implements circular reasoning. For example, it is not permissible for network A to depend on network B if network B depends upon network A because this clearly leads to circular reasoning.

Dependency networks have three basic behaviors:

1. They query antecedent networks on which they depend to determine the state of the latter.
2. They evaluate their own state, given the state of their antecedent networks.
3. They inform higher level networks that depend on them about their state.