concepts.dm.pdsketch.regression_rule.RegressionRuleApplicationExpression

class RegressionRuleApplicationExpression

Bases: object

An abstract regression rule grounding. For example, in (regression-ontop ?x ?y) where ?x and ?y are variables in the context.

Methods

ground(executor)	Ground the regression rule statement.
pddl_str()

Attributes

name	The name of the regression rule.
regression_rule	The regression rule that is applied.
arguments	The arguments of the regression rule.
maintains	The maintain expressions of the regression rule.
serializability	The serializability of the regression rule.
csp_serializability	The continuous serializability of the regression rule.

__init__(regression_rule, arguments, maintains=None, serializability='strong', csp_serializability='none')

Parameters:

• regression_rule (RegressionRule)

• arguments (Sequence[VariableExpression | UnnamedPlaceholder | ValueOutputExpression])

• maintains (Sequence[ValueOutputExpression] | None)

• serializability (SubgoalSerializability | str)

• csp_serializability (SubgoalCSPSerializability | str)

__new__(**kwargs)

ground(executor)

Ground the regression rule statement.

Parameters:

executor (PDSketchExecutor)

Return type:

RegressionRuleApplier

pddl_str()

Return type:

str

arguments: Tuple[VariableExpression | UnnamedPlaceholder | ValueOutputExpression, ...]

The arguments of the regression rule.

csp_serializability: SubgoalCSPSerializability

The continuous serializability of the regression rule.

maintains: Tuple[ValueOutputExpression, ...]

The maintain expressions of the regression rule.

property name: str

The name of the regression rule.

regression_rule: RegressionRule

The regression rule that is applied.

serializability: SubgoalSerializability

The serializability of the regression rule.