Generate a goal stack

Use the defined setting to generate the stack of random goals an agent should complete. This function outputs a list of different instances of the goal-class.

Usage

goal_stack(
  n,
  setting,
  counter = function(n) rnorm(n, 10, 2),
  sort = TRUE,
  starting_position = entrance(setting)[1, ],
  precompute_goal_paths = FALSE,
  middle_edge = FALSE,
  ...
)

Arguments

n

Integer denoting the number of goals to generate.

setting

Object of background-class.

counter

Numeric, vector, or function that defines the counter for each of the goals that are generated. When numeric, each goal will have the same value for counter equal to the value provided to this argument. When a numeric vector, the values of this vector will be iterated as values for the counter in the goals. When a function, a random value for the counter will be generated through the function. For this to work, the function that is provided should take in the input n which defines the number of values to draw from the function. Defaults to \(n) rnorm(n, 10, 2).

sort

Logical denoting whether to order the goal stack in a logical way. Currently implemented in the following way. First, we select the first goal as being the one that is closest by the starting position provided in the argument starting_position. Then, we define each of the next goals as being the one that is closest to the position of the previous goal. Defaults to TRUE.

starting_position

Numeric vector denoting the position at which the agent starts in the room. Defaults to the first entrance of the setting.

precompute_goal_paths

Logical denoting whether to run the find_path for each of the generated goals beforehand. Assumes that the agent does all of the goals in the order of the goal stack. Defaults to FALSE.

middle_edge

Logical denoting whether to sample the goals from the middle of the edge of the objects in the link[predped]{background-class} (TRUE) or to allow the goal locations to fall on all points on these edges (FALSE). Defaults to FALSE.

...

Arguments provided to find_path to precompute the paths that the agents should take to reach their goals. Only used when precompute_goal_paths = TRUE.

Value

List of instances of the goal-class.

See also

background-class goal-class compute_edges create_edges determine_values multiple_goal_stacks

Examples

# Create a setting
my_background <- background(shape = rectangle(center = c(0, 0), 
                                              size = c(2, 2)), 
                            objects = list(circle(center = c(0, 0), 
                                                  radius = 0.5)))

# Create a goal stack containing two goals
stack <- goal_stack(2, my_background)

# Two goals
length(stack)
#> [1] 2
stack
#> [[1]]
#> Goal Attributes 
#> busy: FALSE 
#> counter: 9 
#> done: FALSE 
#> id: goal qcvyr 
#> path:
#>      [,1] [,2]
#> 
#> position: 0.480211 -0.1717481 
#> 
#> For more detailed information, please extract the wanted information from the background directly.
#> 
#> [[2]]
#> Goal Attributes 
#> busy: FALSE 
#> counter: 9 
#> done: FALSE 
#> id: goal hucjy 
#> path:
#>      [,1] [,2]
#> 
#> position: 0.267297 0.4343412 
#> 
#> For more detailed information, please extract the wanted information from the background directly.
#>