concepts.pdsketch.regression_rule.RegressionRuleApplier#

class RegressionRuleApplier[source]#

Bases: object

Methods

Attributes

`goal_expression`
`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')[source]#

Parameters:

regression_rule (RegressionRule)
arguments (Sequence[Variable | TensorValue | Any])
maintains (Sequence[ValueOutputExpression] | None)
serializability (SubgoalSerializability | str)
csp_serializability (SubgoalCSPSerializability | str)

__new__(**kwargs)#

pddl_str()[source]#

Return type:: str

arguments: Tuple[Variable | TensorValue | Any, ...]#: The arguments of the regression rule.

csp_serializability: SubgoalCSPSerializability#: The continuous serializability of the regression rule.

property goal_expression#

maintains: Tuple[ValueOutputExpression, ...]#: The maintain expressions of the regression rule.

regression_rule: RegressionRule#: The regression rule that is applied.

serializability: SubgoalSerializability#: The serializability of the regression rule.