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DevelopingSpecies

RoiArthurB edited this page Feb 22, 2024 · 1 revision

Developing Species

Additional built-in species can be defined in Java in order to be used in GAML models. Additional attributes and actions can be defined. It could be very useful in order to define its behavior thanks to external libraries (e.g. database connection...).

A new built-in species extends the GamlAgent class, which defines the basic GAML agents. As a consequence, new built-in species have all the attributes (name, shape, ...) and actions (die...) of regular species.

Implementation

A new species can be any Java class that:

  • extends the GamlAgent class,
  • begins by the @species: @species(name = "name_of_the_species_gaml"),
@species(name = "multicriteria_analyzer")
public class MulticriteriaAnalyzer extends GamlAgent {

Similarly to skills, a species can define additional attributes and actions.

Additional attributes

Defining new attributes needs:

  • to add @vars (and one embedded @variable per additional attribute) annotation on top of the class,
  • to define @setter and @getter annotations to the accessors methods.

For example, regular species are defined with the following annotation:

@vars({ @variable(name = IKeyword.NAME, type = IType.STRING), @variable(name = IKeyword.PEERS, type = IType.LIST),
	@variable(name = IKeyword.HOST, type = IType.AGENT),
	@variable(name = IKeyword.LOCATION, type = IType.POINT, depends_on = IKeyword.SHAPE),
	@variable(name = IKeyword.SHAPE, type = IType.GEOMETRY) })

And accessors are defined using:

@getter(IKeyword.NAME)
public abstract String getName();

@setter(IKeyword.NAME)
public abstract void setName(String name);

Additional actions

An additional action is a method annotated by the @action annotation.

@action(name = ISpecies.stepActionName)
public Object _step_(final IScope scope) {

Annotations

@species

This annotation represents a "species" in GAML. The class annotated with this annotation will be the support of a species of agents.

This annotation contains:

  • name (string): the name of the species that will be created with this class as base. Must be unique throughout GAML.
  • skills (set of strings, empty by default): An array of skill names that will be automatically attached to this species. Example: @species(value="animal" skills={"moving"})
  • internal (boolean, false by default): whether this species is for internal use only.
  • doc (set of @doc, empty by default): the documentation attached to this operator.

All these annotations are defined in the GamlAnnotations.java file of the msi.gama.processor plug-in.

  1. What's new (Changelog)
  1. Installation and Launching
    1. Installation
    2. Launching GAMA
    3. Updating GAMA
    4. Installing Plugins
  2. Workspace, Projects and Models
    1. Navigating in the Workspace
    2. Changing Workspace
    3. Importing Models
  3. Editing Models
    1. GAML Editor (Generalities)
    2. GAML Editor Tools
    3. Validation of Models
  4. Running Experiments
    1. Launching Experiments
    2. Experiments User interface
    3. Controls of experiments
    4. Parameters view
    5. Inspectors and monitors
    6. Displays
    7. Batch Specific UI
    8. Errors View
  5. Running Headless
    1. Headless Batch
    2. Headless Server
    3. Headless Legacy
  6. Preferences
  7. Troubleshooting
  1. Introduction
    1. Start with GAML
    2. Organization of a Model
    3. Basic programming concepts in GAML
  2. Manipulate basic Species
  3. Global Species
    1. Regular Species
    2. Defining Actions and Behaviors
    3. Interaction between Agents
    4. Attaching Skills
    5. Inheritance
  4. Defining Advanced Species
    1. Grid Species
    2. Graph Species
    3. Mirror Species
    4. Multi-Level Architecture
  5. Defining GUI Experiment
    1. Defining Parameters
    2. Defining Displays Generalities
    3. Defining 3D Displays
    4. Defining Charts
    5. Defining Monitors and Inspectors
    6. Defining Export files
    7. Defining User Interaction
  6. Exploring Models
    1. Run Several Simulations
    2. Batch Experiments
    3. Exploration Methods
  7. Optimizing Model Section
    1. Runtime Concepts
    2. Analyzing code performance
    3. Optimizing Models
  8. Multi-Paradigm Modeling
    1. Control Architecture
    2. Defining Differential Equations
  1. Manipulate OSM Data
  2. Diffusion
  3. Using Database
  4. Using FIPA ACL
  5. Using BDI with BEN
  6. Using Driving Skill
  7. Manipulate dates
  8. Manipulate lights
  9. Using comodel
  10. Save and restore Simulations
  11. Using network
  12. Headless mode
  13. Using Headless
  14. Writing Unit Tests
  15. Ensure model's reproducibility
  16. Going further with extensions
    1. Calling R
    2. Using Graphical Editor
    3. Using Git from GAMA
  1. Built-in Species
  2. Built-in Skills
  3. Built-in Architecture
  4. Statements
  5. Data Type
  6. File Type
  7. Expressions
    1. Literals
    2. Units and Constants
    3. Pseudo Variables
    4. Variables And Attributes
    5. Operators [A-A]
    6. Operators [B-C]
    7. Operators [D-H]
    8. Operators [I-M]
    9. Operators [N-R]
    10. Operators [S-Z]
  8. Exhaustive list of GAMA Keywords
  1. Installing the GIT version
  2. Developing Extensions
    1. Developing Plugins
    2. Developing Skills
    3. Developing Statements
    4. Developing Operators
    5. Developing Types
    6. Developing Species
    7. Developing Control Architectures
    8. Index of annotations
  3. Introduction to GAMA Java API
    1. Architecture of GAMA
    2. IScope
  4. Using GAMA flags
  5. Creating a release of GAMA
  6. Documentation generation

  1. Predator Prey
  2. Road Traffic
  3. 3D Tutorial
  4. Incremental Model
  5. Luneray's flu
  6. BDI Agents

  1. Team
  2. Projects using GAMA
  3. Scientific References
  4. Training Sessions

Resources

  1. Videos
  2. Conferences
  3. Code Examples
  4. Pedagogical materials
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