Whereas STRIPS is an action-centric representation, a feature-centric representation is more flexible, as it allows for conditional effects, and non-local effects.

A feature-based representation of actions models

• •

  the precondition of each action

• •

  for each feature, the feature values in the next state as a function of the feature values of the previous state and the action.

The feature-based representation of actions uses definite clauses to specify the value of each variable in the state resulting from an action. The bodies of these rules can include propositions about the action carried out and propositions about values of features in the previous state. We assume these propositions can be equalities and inequalities between features and values.

The rules have two forms:

• •

  A causal rule specifies when a feature gets a new value.

• •

  A frame rule specifies when a feature keeps its value.

It is useful to think of these as two separate cases: what makes the feature change its value, and what makes it keep its value.

The feature-based representation is more powerful than the STRIPS representation; it can represent anything representable in STRIPS, but can also represent conditional effects. It may be more verbose because it requires explicit frame axioms, which are implicit in the STRIPS representation.

The mapping from STRIPS to the feature-based representation for Boolean features is as follows. If the effect of an action $act$ is $\{e_1,\mathrm{\dots },e_k\}$, the STRIPS representation is equivalent to the causal rules

for each $e_i$ that is made true by the action and the frame rules

for each condition $c$ that does not involve a variable on the effects list. Thus each $e_i$ that assigns a feature to be false does not result in a rule. The precondition of each action is the same in both representations. Non-Boolean features may require multiple rules for the different values of the feature.

A conditional effect of an action depends on the value of other features. The feature-based representation is able to specify conditional effects, whereas STRIPS cannot represent these directly. Example 6.6 shows how to represent in STRIPS the action moving clockwise, where the effect depends on the previous state, by inventing new actions. Example 6.7 shows how the feature-based representation can represent actions without needing to invent those new actions by adding conditions to the rules. The feature-based representation also allows for non-local effects, as in the following example.