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Comprehensive Umgebungsmodellierung Tools for Every Need

Get access to Umgebungsmodellierung solutions that address multiple requirements. One-stop resources for streamlined workflows.

Umgebungsmodellierung

  • JaCaMo

    JaCaMo is a multi-agent system platform integrating Jason, CArtAgO, and Moise for scalable, modular agent-based programming.
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    What is JaCaMo?
    JaCaMo provides a unified environment for designing and running multi-agent systems (MAS) by integrating three core components: the Jason agent programming language for BDI-based agents, CArtAgO for artifact-based environmental modeling, and Moise for specifying organizational structures and roles. Developers can write agent plans, define artifacts with operations, and organize groups of agents under normative frameworks. The platform includes tooling for simulation, debugging, and visualization of MAS interactions. With support for distributed execution, artifact repositories, and flexible messaging, JaCaMo enables rapid prototyping and research in areas like swarm intelligence, collaborative robotics, and distributed decision-making. Its modular design ensures scalability and extensibility across academic and industrial projects.
    JaCaMo Core Features
    • BDI-based agent programming with Jason
    • Artifact environment modeling with CArtAgO
    • Organizational specification using Moise
    • Command-line interface and IDE support
    • Simulation and debugging tools
    • Distributed execution and messaging
    JaCaMo Pro & Cons

    The Cons

    No direct pricing information available.
    No mobile or browser extension applications found.
    May have a steep learning curve due to its complex multi-agent oriented programming paradigm.

    The Pros

    Supports comprehensive multi-agent system programming including agents, environment, and organization.
    Designed for applications demanding autonomy, decentralization, coordination, and openness.
    Open-source with an active GitHub repository.
    Provides educational resources and courses for multi-agent system learning.
    Includes a command line interface to create, run, and manage multi-agent applications.
    Supports integration with frameworks like ROS for autonomous robot development.

  • JASA

    This Java-based agent framework enables developers to create customizable agents, manage messaging, lifecycles, behaviors, and simulate multi-agent systems.
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    What is JASA?
    JASA provides a comprehensive set of Java libraries for building and running multi-agent system simulations. It supports agent lifecycle management, event scheduling, asynchronous message passing, and environment modeling. Developers can extend core classes to implement custom behaviors, integrate external data sources, and visualize simulation outcomes. The framework’s modular design and clear API documentation facilitate rapid prototyping and scalability, making it suitable for academic research, teaching, and proof-of-concept development in agent-based modeling.

  • Multi Agent Simulation

    A Python-based framework enabling creation and simulation of AI-driven agents with customizable behaviors and environments.
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    What is Multi Agent Simulation?
    Multi Agent Simulation offers a flexible API to define Agent classes with custom sensors, actuators, and decision logic. Users configure environments with obstacles, resources, and communication protocols, then run step-based or real-time simulation loops. Built-in logging, event scheduling, and Matplotlib integration help track agent states and visualize results. The modular design allows easy extension with new behaviors, environments, and performance optimizations, making it ideal for academic research, educational purposes, and prototyping multi-agent scenarios.
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