Add a algorithm to problem and stores it on disk.
addProblem(
reg,
id,
static = NULL,
dynamic = NULL,
seed = NULL,
overwrite = FALSE
)
Registry.
[character(1)
]
Name of problem.
[any]
Static part of problem that never changes and is not dependent on parameters.
Default is NULL
.
[function(job, static, ...)
]
R generator function that creates dynamic / stochastic part of problem instance, which might be dependent on parameters.
First parameter job
is a Job
object, second is static problem part static
.
Further parameters from design are passed to ... argument on instance creation time.
The arguments job
and static
may be omitted.
To retrieve job informations from the job
object
see the documentation on ExperimentJob.
Default is NULL
.
[integer(1)
]
Start seed for this problem. This allows the “synchronization” of a stochastic
problem across algorithms, so that different algorithms are evaluated on the same stochastic instance.
The seeding mechanism works as follows, if a problem seed is defined:
(1) Before the dynamic part of a problem is instantiated,
the seed of the problem + replication - 1 is set, so for the first
replication the exact problem seed is used. (2) The stochastic part of the problem is
instantiated (3) From now on the usual experiment seed of the registry is used,
see ExperimentRegistry
.
If seed
is set to NULL
this extra problem seeding is switched off, meaning
different algorithms see different stochastic versions of the same problem.
Default is NULL
.
[logical(1)
]
Overwrite the problem file if it already exists?
Default is FALSE
.
[character(1)
]. Invisibly returns the id.
Other add:
addAlgorithm()
,
addExperiments()