Arg2P is an implementation of the ASPIC+ framework for structured argumentation, which reads assumption-based and abstract frameworks as well. Built on top of the tuProlog engine, it runs on the JVM, in JavaScript (Node.js and browsers) and in Python, with the same API; its solver runs in the browser, in VS Code, and for AI assistants.

The documentation starts from Getting Started.

Installing

| | | | --- | --- | | JVM (Gradle, Maven Central) | implementation("it.unibo.tuprolog.argumentation:arg2p-jvm:<VERSION>") | | JavaScript (npm) | npm install @tuprolog/arg2p | | Python (PyPI) | pip install arg2p (the wheel bundles a Java runtime) | | Browser | the Web Playground: nothing to install | | VS Code | the extension | | Claude Code | /plugin install arg2p --marketplace tuProlog/arg2p-kt | | Codex | codex plugin marketplace add tuProlog/arg2p-kt, then install arg2p from /plugins |

<VERSION> is the latest release, shown by the Maven Central badge above. See Execution for a first program on each platform, the playground, the extension of VS Code, and the plugin and MCP server of Arg2P for AI assistants (the other clients, and the server alone).

Issue tracking

If you encounter any issues, please report them on the GitHub Issues page.
Your feedback helps improve the project!

References

Arg2P is described in:

• Roberta Calegari, Andrea Omicini, Giuseppe Pisano, Giovanni Sartor. Arg2P: an argumentation framework for explainable intelligent systems. Journal of Logic and Computation, 32(2):369–401, 2022. doi:10.1093/logcom/exab089
• Giuseppe Pisano. Argumentation for legal reasoning: meta-models, technology and beyond. PhD thesis, Alma Mater Studiorum — Università di Bologna, 2024. doi:10.48676/unibo/amsdottorato/11671

Individual features — burden of persuasion, defeasible preferences, modularity, causality, distributed reasoning — have their own papers, listed on the References page of the wiki.

Cite me

If you use Arg2P in academic work, please cite:

@article{arg2p,
  author  = {Calegari, Roberta and Omicini, Andrea and Pisano, Giuseppe and Sartor, Giovanni},
  title   = {{Arg2P}: an argumentation framework for explainable intelligent systems},
  journal = {Journal of Logic and Computation},
  volume  = {32},
  number  = {2},
  pages   = {369--401},
  year    = {2022},
  doi     = {10.1093/logcom/exab089}
}

@phdthesis{pisano2024argumentation,
  author  = {Pisano, Giuseppe},
  title   = {Argumentation for legal reasoning: meta-models, technology and beyond},
  school  = {Alma Mater Studiorum --- Universit\`a di Bologna},
  year    = {2024},
  doi     = {10.48676/unibo/amsdottorato/11671}
}