cff-version: 1.2.0
message: If you use this dataset, please cite both the dataset and the accompanying paper.
type: dataset
title: 'Persona-Profiled Agent Predictability: dataset for "Personality-Profiled Virtual Agents Are More Predictable: The Constraint-Entropy Tradeoff for Trustworthy Agent Design"'
version: 1.0.0
date-released: '2026-11-12'
license: CC-BY-4.0
authors: &id001
- family-names: Toxtli
  given-names: Carlos
  affiliation: Clemson University
  orcid: https://orcid.org/0000-0002-9430-2661
- family-names: Delaflor
  given-names: Manuel
  affiliation: Metacognition Institute
abstract: 'Session-level data from the predictability experiment comparing persona-profiled and unprofiled LLM agents: trial summaries, test records, behavioral-consistency and persona-fidelity metrics, intermediate-temperature results, and a 36-pair validation of the LLM judge against an independent human rater (scores, judge scores, results and rater instructions).'
keywords:
- virtual-agents
- persona
- predictability
- multi-agent
- llm-agents
- llm-as-a-judge
doi: 10.5281/zenodo.24179036
url: https://huggingface.co/datasets/ai4he/persona-profiled-agents-predictability
preferred-citation:
  type: conference-paper
  title: 'Personality-Profiled Virtual Agents Are More Predictable: The Constraint-Entropy Tradeoff for Trustworthy Agent Design'
  authors: *id001
  year: 2026
  collection-title: ACM International Conference on Intelligent Virtual Agents (IVA 2026)
  doi: 10.1145/3806774.3827973