Skip to content

PlatformAgent

AlexisDrogoul edited this page Nov 7, 2026 · 1 revision

The gama platform agent

The unique gama agent represents the running GAMA platform. In addition to platform information, it provides explicit operations for preferences, model execution, tests, and validation. These actions can be called from model code or from the interactive console while an experiment is active.

Preferences

gama.preferences() lists preferences exposed to GAML with their current values, types, constraints, default values, and restart requirements. Pass a key to inspect one preference:

write gama.preferences("pref_check_memory");

Preference updates are in-memory by default. Set persist: true to write the change to the user's preference store:

gama.set_preference("pref_check_memory", false);
gama.set_preference("pref_check_memory", true, persist: true);
gama.reset_preference("pref_check_memory", persist: true);

The in-memory value is restored when the active experiment closes; a persistent write remains saved in the preference store. Only preferences already marked as GAML-accessible can be inspected or changed this way.

Opening experiments and playable packages

gama.open(model, experiment) opens an experiment from a model path. If another experiment is active, GAMA asks before closing it. The optional confirm argument can be set to false for deliberate scripted experiment chains:

gama.open("/workspace/Project/model.gaml", "first");
gama.open("/workspace/Project/model.gaml", "second", confirm: false);

Model paths can be absolute file paths or workspace-relative paths. Opening an experiment requires the GUI workbench and does not import the model into the workspace.

A playable .gamx archive is launched separately in its isolated player process:

gama.play_package("/path/to/model.gamx");

Playable packages are not regular .gaml files and cannot be launched through this action in headless mode.

Running tests and validating models

gama.run_tests(model) synchronously runs the model's test experiments headlessly and returns a summary for each experiment. gama.validate_workspace() compiles every model discovered in the current workspace and returns a success or diagnostic string per model. gama.validate_code(code, syntax_only: true) validates a GAML snippet without executing it:

write gama.run_tests("/workspace/Project/model.gaml");
write gama.validate_workspace();
write gama.validate_code("1 + 1", syntax_only: true);

Workspace validation and test execution can take time on large workspaces. Validation reports compilation diagnostics; it does not execute models. The interactive console itself still requires an active experiment; these actions do not turn it into a standalone platform shell.

  1. What's new (Changelog)
  2. Migration Guide (2025-06 → 2026-06)
  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
    9. Experiment agent: GAML controls and status
  5. Running Headless
    1. Getting Started
    2. Headless Legacy
    3. Headless Batch
  6. Exporting Projects As Simulation Launchers
  7. Preferences
  8. gama platform agent
  9. 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. Classes and Objects
    1. Class Definition and Instantiation
    2. Attributes and Actions
    3. Inheritance
    4. Virtual Classes
    5. Advanced Features
  7. Exploring Models
    1. Run Several Simulations
    2. Batch Experiments
    3. Exploration Methods
  8. Optimizing Models
    1. Runtime Concepts
    2. Analyzing code performance
    3. Optimizing Models
  9. Multi-Paradigm Modeling
    1. Control Architecture
    2. Defining Differential Equations
  1. Manipulate OSM Data
  2. Cleaning OSM Data
  3. Diffusion
  4. Using Database
  5. Using Dataframes
  6. Using FIPA ACL
  7. Using BDI with BEN
  8. Using Driving Skill
  9. Manipulate dates
  10. Manipulate lights
  11. Using comodel
  12. Save and restore Simulations
  13. Using network
  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. Stats Extension
  8. Sound Extension
  9. BDI Extension
  10. FIPA Skill
  11. Expressions
    1. Literals
    2. Units and Constants
    3. Pseudo Variables
    4. Variables And Attributes
    5. Operators (Definition)
    6. Operators [A-A]
    7. Operators [B-C]
    8. Operators [D-H]
    9. Operators [I-M]
    10. Operators [N-R]
    11. Operators [S-Z]
  12. Exhaustive list of GAMA Keywords
  1. Installing the development version
  2. Introduction to GAMA Java API
    1. Architecture of GAMA
    2. IScope
  3. 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
  4. Using GAMA flags
  5. Export plugin : Technical Documentation
  6. Creating a release of GAMA
  7. Documentation generation

  1. Predator Prey
  2. Road Traffic
  3. Incremental Model
  4. Luneray's flu
  5. BDI Agents
  6. Forager RL
  7. SIR Analysis
  8. 3D Model

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

Resources

  1. Videos
  2. Conferences
  3. Pedagogical materials

Clone this wiki locally