Active Inference Power Suite: Conditional Statistical Power under Controlled Generative Settings

Statistical power is an investigator-facing operating characteristic of an adaptive-study design. Before simulation, the investigator fixes an agent-side model, evaluator-side process, testing setting, policy, and replication plan. Each embedded agent acts only on visible history; simulated hidden truth is retained for scoring. active_inference_power makes that conditional estimand inspectable. The suite combines fixed-horizon procedures, analytic references, dependence/calibration experiments, and a discrete-state active-inference agent checked against a binary oracle. It extends this to action loops with sensing reliability, latent context, target choice, cost, and stopping. The study distinguishes model-relative posterior belief from calibrated p-value and likelihood-ratio e-process evidence. It compares Benjamini–Hochberg (BH) false discovery rate (FDR) procedures with family-wise error rate (FWER) alternatives, and separates either evidence object from online FDR procedure-specific accounting. Results are scenario-indexed finite-simulation estimates with Monte Carlo standard error (MCSE) and declared error, dependence, filtration, and optional-stopping boundaries; they do not assign a universal power value to an agent, task environment, or active inference. Instead, they support auditable comparisons among explicitly declared adaptive-study designs. Contracts, seed schedules, certificates, figures, claim ledger, and rendered manuscript form a linked evidence chain, allowing readers to trace each claim to its design and artifact. Source and release materials are available at the verified GitHub repository ActiveInferenceInstitute/active_inference_power.

Active Inference Power Suite v1.0.0 is a source-bound release of an adaptive-study design suite. It reports scenario- and policy-indexed finite-simulation operating characteristics; it does not claim a universal "power of active inference."

• Source repository and exact release: https://github.com/ActiveInferenceInstitute/active_inference_power/releases/tag/v1.0.0
• Concept DOI (release family): 10.5281/zenodo.21695160
• Version DOI (this immutable archive): 10.5281/zenodo.21695161
• Zenodo record: https://zenodo.org/records/21695161
• PDF SHA-256: 24fa25a4f29affcfd92c8c001ff6487a0c36960c6b4f38ed4419984fc8743cbf

The uploaded PDF, exact tag-derived source archive, release manifest, renderer provenance, and final review receipt make the release auditable. The evidence boundary remains finite, scenario-specific simulation rather than a universal theorem or deployment claim.