Learn ANYLOGIC-SCRIPTING with Real Code Examples

AnyLogic Scripting enables fine-grained control over agents, events, and processes using Java code.

It allows extending simulation models with custom logic, calculations, and integration with external data or APIs.

Used in business, logistics, manufacturing, healthcare, and supply chain simulations.

Supports object-oriented and event-driven programming inside the simulation environment.

Widely adopted for research, industrial process optimization, and educational simulation projects.

Agent behavior methods and custom actions

Java code in event triggers and statecharts

Dynamic variable calculation and monitoring

Custom visualization and dashboards

Integration with AnyLogic experiments (Monte Carlo, optimization)

Agent - an autonomous entity with state and behavior

Event - triggers that execute code at specific times

Statechart - defines agent states and transitions

Variable - stores dynamic values within agents or environment

Function - reusable Java method inside the model

Main model file (.alp) containing agents and environment

Embedded Java code for agent behavior

Experiment definitions for batch runs

Data import/export configurations

Visualization and reporting setup

Define agents and environment in visual editor

Add custom behavior using AnyLogic scripting

Configure events, statecharts, and transitions

Run simulations and adjust parameters

Analyze results and visualize outputs

Beginner: simple agent interactions with built-in blocks

Intermediate: add small custom actions using Java code

Advanced: complex decision logic, events, and custom charts

Expert: integrate external databases, APIs, or optimization algorithms

Architect: design full-scale multimethod simulations with modular Java scripting

AnyLogic scripting vs visual blocks: more flexibility, higher complexity

AnyLogic scripting vs Python: Java-based, directly integrated with simulation

AnyLogic scripting vs NetLogo: more industrial-grade, supports multimethod simulation

AnyLogic scripting vs Simulink: focuses on discrete-event and agent-based, less continuous math modeling

AnyLogic scripting vs R: better for dynamic simulation than statistical computation

2000 - AnyLogic first release by XJ Technologies

2005 - Agent-based modeling scripting introduced

2010 - Multimethod simulation and Java integration enhanced

2015 - Cloud experiments and optimization scripting added

2020 - Improved visualization and analytics scripting

2024 - Latest IDE updates and Java 17 support

2025 - Continued focus on multimethod simulation and performance

Agent - autonomous simulation entity

Event - triggers code at a specific time

Statechart - defines agent state and transitions

Variable - stores dynamic values

Function - reusable Java code block in model