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Behavioral and computational scientist. I study how information is distributed, interpreted, and transformed through networks, and how communication structure shapes judgment, coordination, and collective behavior across human, organizational, and AI systems.

The work combines experiments, network analysis, measurement, simulation, statistical inference, and computational systems. Four lines are active: machine-agent networks, information transformation and provenance, simulation as a way of separating mechanisms that produce similar visible outcomes, and measurement of cultural structure.

graystoneindustries.co

Research code and replication materials

Repository Paper
m2m-collective-belief-dynamics Communication content and local connectivity shape collective accuracy in networks of machine agents
m2m-information-mutation Communication architecture shapes information mutation in AI-agent networks
m2m-bavelas-groups Communication topology shapes collective problem solving in networks of machine agents
structural-legibility-prototype Message residue preserves traces of hidden communication structure
bfg-corrective-replicator Error correction accelerates multi-target adaptation under compatible constraints
schelling-informational-assumptions The informational assumptions of Schelling segregation
memes-structural-signals Memes as structural signals

Research infrastructure

manuscript-u recommends where to submit an academic manuscript, returning ranked journals with fit scores, desk-rejection risk, and revision culture notes grounded in data fetched at query time.

org-signal computes a social-network graph from a Slack workspace export, including betweenness and eigenvector centrality, reciprocity, and bridging, and writes reports from it. Everything runs in the browser.

Talks

ai-credibility-networked-systems is a fifteen-minute talk on credibility and evaluation in systems of interacting agents, built as a self-driving browser presentation with an animation for each of seven research questions.

Applied software

Browser-native recommendation tools, each a two-stage reasoning pipeline over live web search with explicit confidence scoring. No backend, no build step.

Other

daily-digest-script assembles a daily email and Slack digest.

Popular repositories Loading

  1. schelling-informational-assumptions schelling-informational-assumptions Public

    Agent-based model and replication archive for 'The Informational Assumptions of Schelling Segregation'. Decomposes common observation, common categorization, and coordinated action, with agents inf…

    Python

  2. m2m-bavelas-groups m2m-bavelas-groups Public

    Replication materials for 'Communication topology shapes collective problem solving in networks of machine agents'. Applies the Bavelas communication network paradigm to groups of large language mo…

    Python

  3. latent-diffusion-collective-action latent-diffusion-collective-action Public archive

    Superseded. Replication materials for the earlier 'Latent Diffusion and the Assembly of Collective Action' study. This line was retired and replaced by later compositional latent diffusion work. Ke…

    Python

  4. memes-structural-signals memes-structural-signals Public

    Computational proof-of-concept supporting 'Memes as Structural Signals: A Chemical Model of Interpretive Compatibility' (Gladstone & Thompson), accepted at Biosemiotics. Pharmacophore-reactome SAR …

    Python

  5. m2m-information-mutation m2m-information-mutation Public

    Replication materials for 'Communication architecture shapes information mutation in AI-agent networks'. Simulation code, data, and figures covering 6 topologies of LLM-agent transmission chains, 5…

    HTML

  6. structural-legibility-prototype structural-legibility-prototype Public

    Research prototype for 'Message residue preserves traces of hidden communication structure'. Tests whether communication topologies leave detectable, discriminative residues in transmitted messages…

    Python