organisation = "IEEE Neural Network Council (NNC), Evolutionary
Programming Society (EPS), Institution of Electrical
Engineers (IEE)",
publisher = "IEEE Press",
keywords = "genetic algorithms, genetic programming, computational
linguistics, grammars, learning (artificial
intelligence), search problems, AI planning system,
EVOCK, Evolution of Control Knowledge, GP based system,
PRODIGY, ad-hoc mechanisms, blocksworld domain, control
knowledge learning, control rule language, control rule
syntax, control rules, grammar approach flexibility,
grammar specific, grammars, language restrictions,
search space, standard GP, standard select type",
abstract = "In standard GP there are no constraints on the
structure to evolve: any combination of functions and
terminals is valid. However, sometimes GP is used to
evolve structures that must respect some constraints.
Instead of ad-hoc mechanisms, grammars can be used to
guarantee that individuals comply with the language
restrictions. In addition, grammars permit great
flexibility to define the search space. EVOCK
(Evolution of Control Knowledge) is a GP based system
that learns control rules for PRODIGY, an AI planning
system. EVOCK uses a grammar to constrain individuals
to PRODIGY 4.0 control rule syntax. The authors
describe the grammar specific details of EVOCK. Also,
the grammar approach flexibility has been used to
extend the control rule language used by EVOCK in
earlier work. Using this flexibility, tests were
performed to determine whether using combinations of
several types of control rules for planning was better
than using only the standard select type. Experiments
have been carried out in the blocksworld domain that
show that using the combination of types of control
rules does not get better individuals, but it produces
good individuals more frequently",
notes = "CEC-2001 - A joint meeting of the IEEE, Evolutionary
Programming Society, Galesia, and the IEE.