Published June 3, 2026 | Version v2.4
Report Open

Appearance–Behavior Framework v2.3: Counterfactual Intervention Simulation and Adaptive Decision Support

Authors/Creators

  • 1. SD Lab LLC

Description

ABF v2.3 advances the real-time Digital Twin architecture of the Appearance–Behavior Framework by introducing counterfactual intervention simulation and adaptive decision support, extending the framework from monitoring to action-oriented behavioral forecasting.

This release presents four tightly integrated contributions:

Counterfactual Intervention Simulation Framework (Fig. 33) — a principled framework for evaluating candidate interventions through posterior predictive simulation with explicit uncertainty quantification.

Intervention Trajectory Comparison (Fig. 34) — quantitative comparison of counterfactual BTRS trajectories, critical transition time (τ̂crit) distributions, uncertainty summaries, and risk-threshold exceedance probabilities across alternative intervention candidates.

Decision Support Dashboard (Fig. 35) — an integrated Digital Twin interface combining subject monitoring, intervention ranking, uncertainty decomposition, feature sensitivity analysis, and scenario controls.

RL Pilot Demonstration (Fig. 36) — a proof-of-concept adaptive intervention sequencing framework using a Constrained Actor-Critic (PPO) policy trained within a synthetic ABF simulation environment.

ABF v2.3 represents the transition from predictive monitoring to adaptive decision support. The framework enables quantitative comparison of alternative intervention scenarios while explicitly propagating uncertainty through the forecasting process.

All figures, simulations, and numerical results are illustrative and simulation-derived. ABF v2.3 is a decision-support framework and does not constitute a diagnostic, clinical intervention, or causal inference system. Candidate interventions are illustrative categories intended for methodological demonstration only. Real-world deployment requires prospective empirical validation and domain-specific evaluation.

This release includes:

  • Full manuscript (33 pages)
  • Figures 1–36
  • ABF v2.3 demo script
  • Counterfactual intervention simulation framework
  • Decision support dashboard
  • Reinforcement learning pilot demonstration

Files

ABF_v2_3_Intervention_Optimization_and_Decision_Support.pdf

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Additional details

Related works

Is new version of
Report: 10.5281/zenodo.20528264 (DOI)

Software

Programming language
Python