DALI - Multi-Agent System Framework

DALI Multi Agent Systems Framework

DALI is a meta interpreter built on top of SICStus Prolog ® (at the moment).

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Overview

DALI is a powerful framework that extends standard logic programming with reactive and proactive capabilities. It allows for the creation of intelligent agents that can:

• React to external events.
• Proactively pursue goals.
• Maintain internal state and memory.
• Communicate using FIPA-compliant patterns.

Documentation Index

Repository Markdown guides and notes:

General Notes

• Examples Overview
• Warnings and Timers
• Double Events
• Additional Projects

Unix

• Unix Basic Guide
• Unix Advanced Guide
• Unix Advanced Types
• Unix Advanced Instances
• Unix Dashboard Guide

Windows

• Windows Basic Guide
• Windows Advanced Guide
• Windows Advanced Types
• Windows Advanced Instances

Docker

• Docker Guide
• Docker Installer Notes

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Prerequisites

DALI requires SICStus Prolog to be installed and activated on your system.

1. Download & Install

Download the SICStus Prolog interpreter from the version offered by the University by contacting Prof. Giovanni De Gasperis at [email protected].

2. License Activation

You must activate SICStus using the site-wide license provided by the University. Follow the installer instructions to enter the license key.

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Quick Start

DALI supports native execution on Windows and Unix-like systems, and also provides a Docker-based setup for containerized runs. Choose the method that best fits your environment.

Windows

No complex setup is required. The Windows scripts feature dynamic discovery of SICStus Prolog and streamlined execution.

Warning

SICStus Prolog License & Version Availability
The University has purchased licenses for SICStus Prolog 4.6.0. However, the official SICStus website currently only provides downloads for more recent versions (4.8 to 4.10).
To obtain the installer for the correct version (4.6.0), please contact Prof. Giovanni De Gasperis at [email protected].

1. Navigate to examples/win/basic.
2. Double-click startmas.bat.
3. Descriptive windows for the Server, User agent, and Agents will open automatically.

Unix (Linux / macOS / WSL2)

DALI leverages tmux for a powerful, tiled interface in Unix environments.

1. Navigate to examples/unix/advanced.
2. Run the startup script:

   ./startmas.sh

3. A tmux session will launch with a tiled layout for all MAS components.

Docker

For a containerized setup, use the material in examples/docker/.

1. See Docker Guide for setup, build, and runtime instructions.
2. See Docker Installer Notes for the required SICStus installer placement.

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Testing your MAS

Once the MAS is running, you can test the communication between agents using the User Console (or the Web Dashboard).

1. In the User Console window (Prolog prompt), identify the target agent:

   agent1.

2. Identify yourself:

   user.

3. Send a message (e.g., the go event):

   send_message(go, user).

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DALI Web Dashboard

Monitor and interact with your MAS through a modern, Zero-Config web interface. The dashboard automatically discovers agents and provides real-time logs and command input.

Launching the Dashboard

From a Unix-like environment (including WSL2):

cd examples/unix
./run.sh --folder ./advanced

Access the UI at http://localhost:5000.

For more detailed information on available CLI flags and internal functionality, see DASHBOARD.md.

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Repository Structure

The repository is organized to support different levels of complexity and deployment environments:

• src/: The core DALI engine and meta-interpreter.
• examples/:
  • win/: Native Windows .bat architectures.
    • basic/: Simple, flat agent structures (perfect for beginners).
    • advanced/: Complex structures using agent types and instances
  • unix/: Advanced tmux and bash architectures.
    • basic/: Simple, flat agent structures (perfect for beginners).
    • advanced/: Complex structures using agent types and instances.
    • ui/: Web dashboard utilities and documentation for Unix-based runs.
  • docker/: Containerized environment for running DALI with Docker.
  • more/: Additional projects, references, and linked examples.
• img/: Screenshots and visual documentation assets.
• docs/: Technical documentation and research papers.

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Release History

Check the release history page for more information.

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Development Setup

To create your own DALI MAS from scratch, use an existing example as a boilerplate:

1. Create a project folder (e.g., projectFolder).
2. Copy the core engine — place the DALI/src folder inside your projectFolder.
3. Initialize your application — create a sub-folder for your DALI app (e.g., DALIappFolder).
4. Copy a boilerplate — use examples/unix/advanced or examples/unix/basic if on Unix, or examples/win/advanced or examples/win/basic on Windows as a starting point.
5. Define your agents:
   • Advanced layout: define agent types in mas/types/ and instances in mas/instances/.
   • Basic layout: place all agent .txt files directly in mas/.
6. Run the startup script — the script will automatically discover your SICStus installation and launch the MAS.

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Examples of Applications

• in Robotics: coordination among store delivery robots:

  

  Video from S. Valentini.

• F1 Race Simulator: A Formula 1 race simulator where DALI agents control racing cars in a competitive environment.

  

  Video from M. Piccirilli.

References

• DALI 1.0 original URL(no more active): http://www.di.univaq.it/stefcost/Sito-Web-DALI/WEB-DALI
• COSTANTINI, Stefania. The DALI Agent-Oriented Logic Programming Language: Summary and References 2015.
• COSTANTINI S, TOCCHIO A. A logic programming language for multi-agent systems. Logics in Artificial Intelligence, Springer Berlin Heidelberg, 2002, pp:1-13.
• COSTANTINI S, TOCCHIO A. The DALI logic programming agent-oriented language. In Logics in Artificial Intelligence Springer Berlin Heidelberg, 2004, pp:685-688.
• COSTANTINI S, TOCCHIO A. DALI: An Architecture for Intelligent Logical Agents. In: AAAI Spring Symposium: Emotion, Personality, and Social Behavior. 2008. pp:13-18.
• BEVAR V, COSTANTINI S, TOCCHIO A, DE GASPERIS G. A multi-agent system for industrial fault detection and repair. In: Advances on Practical Applications of Agents and Multi-Agent Systems. Springer Berlin Heidelberg, 2012. pp:47-55.
• DE GASPERIS, G, BEVAR V, COSTANTINI S, TOCCHIO A, PAOLUCCI A. Demonstrator of a multi-agent system for industrial fault detection and repair. In: Advances on Practical Applications of Agents and Multi-Agent Systems. Springer Berlin Heidelberg, 2012. pp:237-240.
• DE GASPERIS Giovanni. DETF 1st Release (Version 14.08a). Zenodo. , 2014, August 6.
• COSTANTINI, Stefania; DE GASPERIS, Giovanni; NAZZICONE, Giulio. DALI for cognitive robotics: principles and prototype implementation. In: International Symposium on Practical Aspects of Declarative Languages. Springer, Cham, 2017. p. 152-162.
• COSTANTINI, Stefania, DE GASPERIS, Giovanni, PITONI Valentina, SALUTARI Agnese. DALI: A multi agent system framework for the web, cognitive robotic and complex event processing., CILC 2017, 32nd Italian Conference on Computational Logic 26-28 September 2017, Naples, Italy
• RAFANELLI, Andrea; COSTANTINI, Stefania; DE GASPERIS, Giovanni. A Multi-Agent-System framework for flooding events. 2022. WOA 2022: 23rd Workshop From Objects to Agents, September 1–2, Genova, Italy
• COSTANTINI, Stefania. Ensuring trustworthy and ethical behaviour in intelligent logical agents. Journal of Logic and Computation, 2022, 32.2: 443-478.

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Contacts

Giovanni De Gasperis
Email: [email protected]

Distributed under the Apache License 2.0. See LICENSE for more information.

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Contributing

We welcome contributions!

1. Fork the repository.
2. Create your feature branch (git checkout -b feature/fooBar).
3. Commit your changes (git commit -am 'Add some fooBar').
4. Push to the branch (git push origin feature/fooBar).
5. Create a new Pull Request to our dev branch.