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Roberto Brunelli

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#generative ai Open access Sep 2026

BDPD — Be Different Play Differential (computational laboratory, simulation platform, and card game)

BDPD (Be Different Play Differential) is an open-source computational laboratory for the study of common-pool resource dilemmas, governance, Seneca-type collapse dynamics, and the role of heterogeneous generative agents. This deposit archives the source code at tag v1.1.5 as a self-contained snapshot, intended for permanent citation and reproducibility of the five-paper BDPD research series, the ten-lecture mini-course, the research notes, the annotated bibliography, and the fifteen-slide overview pitch — all of which are deposited as siblings on Zenodo and linked back to this software record. Since v1.1.4, this release repairs the governed substrate — a turn that resolves nothing is scored at harvest 0, a declared announcement always reaches the record, and an unattributable fine is fixed — each guarded by a two-sided invariant gate; retires the abandoned GT1 experiment; and adds BDPD⁴ (A Fully Grown Forest of Humbaba), which extends the card game to carry the platform's governance, polycentric and Seneca surfaces together with a reproducible experimental apparatus. Components: a Node.js multi-agent simulation engine (the BDPD Arena) with a polycentric World layer for cross-arena treaties and meta-agent governance, three swappable physics engines (logistic, ladder-perturbation, Bardi/Seneca three-variable ODE); Python heuristic and LLM agents on a uniform message bus; The Forest of Humbaba, a physical card game and its AI-playable digital twin; an experiment runner with sweep, perturbation, and OFAT-robustness pipelines; an annotated documentation site (bdpd.gitlab.io/bdpd); and the rendered PDFs of every BDPD deliverable for offline review. The source repository lives at gitlab.com/bdpd/bdpd. Reproducibility instructions: see docs/experiments/reproduce.md in the archive. Substrate-engine determinism is guaranteed for heuristic players; LLM players require external API keys (deposit ships scripts but not credentials).

Roberto Brunelli · 0 citations
#large language models Open access Sep 2026

BDPD: an opinionated annotated bibliography

An opinionated annotated bibliography for the BDPD project. Each entry contains a full citation, the original abstract (where available, reproduced as academic fair use), and an AI Note — a single-paragraph annotation structured around three frames: what the work argues and with what method; why it is relevant to BDPD (referencing specific BDPD papers, lessons, or empirical findings); and one caveat or scope limit worth keeping in mind. The AI Note annotations are generated by a large language model from the original text of each work; entries cited in the project's published deliverables received a per-citation cross-check audit, with stretched uses flagged and corrected in the corresponding paper text. The bibliography is generated dynamically from the project's master BibTeX file and reflects the state of the BDPD literature at the time of publication.

Roberto Brunelli · 1 citation