Update Agent

Update the current agent by first updating its goal status (i.e., checking how and whether an agent can start interacting with a goal, has to reorient, etc) and then updating its position (i.e., using the utility functions to determine where the agent will move next).

Usage

# S4 method for class 'agent'
update(
  object,
  state,
  background,
  agent_specifications,
  seen,
  velocities = matrix(rep(c(1.5, 1, 0.5), each = 11), ncol = 3),
  orientations = matrix(rep(c(72.5, 50, 32.5, 20, 10, 0, 350, 340, 327.5, 310, 287.5),
    times = 3), ncol = 3),
  close_enough = 2,
  space_between = 1.25,
  precomputed_edges = NULL,
  many_nodes = !is.null(precomputed_edges),
  adaptive_goal_sorting = TRUE,
  standing_start = 0.1,
  time_step = 0.5,
  report = FALSE,
  print_iteration = FALSE,
  cpp = TRUE
)

Arguments

object: Object of the agent-class.
state: Object of the state-class.
background: Object of the background-class.
agent_specifications: List created by the create_agent_specifications function. Contains all information of all agents within the current state and allows for the communication between the predped simulation functions and the m4ma utility functions.
seen: Logical indicating whether the agent can see the path point to which they are currently moving.
velocities: Numeric matrix containing the change in speed for an agent whenever they move to the respective cell of this matrix. Is used to create the cell positions that the agent might move to. Defaults to a matrix in which the columns contain 1.5 (acceleration), 1, and 0.5.
orientations: Numeric matrix containing the change in direction for an agent whenever they move to the respective cell of this matrix. Is used to create the cell positions that the agent might move to. Defaults to a matrix in which the rows contain 72.5, 50, 32.5, 20, 10, 0, 350, 340, 327.5, 310, 287.5 (note that the larger angles are actually the negative symmetric versions of the smaller angles).
close_enough: Numeric denoting how close (in radii) the agent needs to be to an object in order to interact with it. Defaults to 2, meaning the agent can interact with objects at 2 * radius(agent) distance away.
space_between: Numeric denoting the space that should be left between an object and the created path points for the agents (in radii). Defaults to 2.5, meaning a space of 2.5 * radius(agent) is left between an object and the path points agents use in their strategy.
precomputed_edges: Output of compute_edges containing the nodes and edges the agent can use to plan its path. Defauls to NULL, triggering the creation of these edges whenever they are needed.
many_nodes: Logical denoting whether to use the minimal number of nodes or to use many more (see create_edges). Ignored if precomputed_edges is provided. Defaults to FALSE.
adaptive_goal_sorting: Logical denoting whether agents have the ability to change the order of their goals adaptively throughout the simulation. Defaults to TRUE.
standing_start: Numeric denoting the factor of their preferred speed that agents move when they just came from standing still. Defaults to 0.1.
time_step: Numeric denoting the number of seconds each discrete step in time should mimic. Defaults to 0.5, or half a second.
report: Logical denoting whether to report whenever an agent is reorienting. Defaults to FALSE, and is usually not needed as feedback.
print_iteration: Logical denoting whether to report each simulated iteration. Defaults to FALSE, but can be switched off if desired.
cpp: Logical denoting whether to use the Rcpp alternatives for several of the lower-level functions (TRUE) or whether to use the R alternatives instead (FALSE). Defaults to TRUE.

Value

Object of the agent-class.

Usage

Arguments

Value

See also