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3.3.1
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    • Setting up a Konakart environment for testing Akamas
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  • Optimizer
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  1. Akamas Reference
  2. Construct templates
  3. Study template
  4. Steps

Optimize step

Last updated 1 year ago

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An optimize step generates optimized configurations according to the defined optimization strategy. During this step, Akamas AI is used to generate such optimized configurations.

The optimize step has the following structure:

Field
Type
Value restrictions
Is required
Default value
Description

type

string

optimize

yes

The type of the step, in this case, optimize

name

string

yes

The name of the step

runOnFailure

boolean

true false

no

false

The execution policy of the step:

  • false prevents the step from running in case the previous step failed

  • true allows the step to run even if the previous step failed

numberOfExperiments

integer

numberOfExperiments > 0 and

numberOfExperiments >= numberOfInitExperiments

yes

The number of experiments to execute - see below

numberOfTrials

integer

numberOfTrials > 0

no

1

The number of trials to execute for each experiment

numberOfInitExperiments

integer

numberOfInitExperiments < numberOfExperiments

no

10

The number of initialization experiment to execute - see below.

maxFailedExperiments

integer

maxFailedExperiments > 1

no

30

The number of experiment failures (as either workflow errors or constraint violations) to accept before the step is marked as failed

optimizer

string

AKAMAS SOBOL RANDOM

no

AKAMAS

The type of optimizer to use to generate the configuration of the experiments - see below

doNotRenderParameters

string

no

renderParameters

string

no

Optimizer

The optimizer field allows selecting the desired optimizer:

  • AKAMAS identifies the standard AI optimizer used by Akamas

  • SOBOL identifies an optimizer that generates configurations using

  • RANDOM identifies an optimization that generates configurations using random numbers

Notice that SOBOL and RANDOM optimizers do not perform initialization experiments, hence the field numberOfInitExperiments is ignored.

Refer to page Optimizer Options for more configuration options for the optimizer

Failures

The optimize step is fault-tolerant and tries to relaunch experiments on failure. Nevertheless, the step imposes a limit on the number of failed experiments: if too many experiments fail, then the entire step fails too. By default, at most 30 experiments can fail while Akamas is optimizing systems. An experiment is considered failed when it either failed to run (i.e., there is an error in the workflow) or violated some constraint.

Initializations

The optimize step launches some initialization experiments (by default 10) that do not apply the AI optimizer and are used to find good configurations. By default, the step performs 10 initialization experiments.

Initialization experiments take into account bootstrapped experiments, experiments executed in preset steps, and baseline experiments.

Example

The following snippet shows an optimization step that runs 50 experiments using the SOBOL optimizer:

name: "my_optimize" # name of the step
type: "optimize" # type of the step (optimize)
optimizer: "SOBOL"
numberOfExperiments: 50 # amount of experiments to execute
numberOfTrials: 2 # amount of trials for each experiment

Parameters not to be rendered. - see

Parameters to be rendered. - see

Sobol sequences
Parameter rending
Parameter rending