Trial class for running a single simulation

Trial class for running a single simulation

Trial class for running a single simulation

Details

Represents a single run of an AgentBasedModel over time, with customizable interaction and update logic. Tracks time-series observations and outcome measures such as adaptation success and steps to fixation.

Methods

Public methods

• Trial$new()

• Trial$run()

• Trial$add_metadata()

• Trial$get_metadata()

• Trial$get_observations()

• Trial$get_outcomes()

• Trial$get_label()

• Trial$clone()

---

Method new()

Initialize a Trial with a model and functions

Usage

Trial$new(model, metadata = list())

Arguments

model

An AgentBasedModel instance

metadata

Label-value metadata store for trial information

---

Method run()

Run the model and collect results

Usage

Trial$run(
  stop = 50,
  legacy_behavior = "Legacy",
  adaptive_behavior = "Adaptive"
)

Arguments

stop

Either integer for max steps, or predicate function

legacy_behavior

The maladaptive behavior treated as "adaptation failure"

adaptive_behavior

The behavior treated as "adaptation success" Add or update metadata in a Trial object

---

Method add_metadata()

Usage

Trial$add_metadata(new_metadata)

Arguments

new_metadata

A named list to merge into existing metadata

self

The Trial object

---

Method get_metadata()

Return the trial's metadata as a named list.

Usage

Trial$get_metadata()

Returns

A named list containing metadata values for this trial, including any scalar or function-valued inputs specified during setup.

---

Method get_observations()

Return the observation data

Usage

Trial$get_observations()

---

Method get_outcomes()

Return outcome measures

Usage

Trial$get_outcomes()

---

Method get_label()

Return the label for this trial (if set)

Usage

Trial$get_label()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

Trial$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.