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  "id": "oai:papers.qnfo.org:counterfactual-reasoning-as-epistemically-necessary-in-deterministic-agents",
  "slug": "counterfactual-reasoning-as-epistemically-necessary-in-deterministic-agents",
  "title": "Counterfactual Reasoning as Epistemically Necessary in Deterministic Agents",
  "authors": [
    "Rowan Brad Quni-Gudzinas"
  ],
  "abstract": "Deterministic physical theories deny genuine alternatives, yet agents must act under incomplete knowledge of hidden causal variables that fix outcomes. Existing decision‑theoretic analyses of counterfactuals presuppose metaphysical indeterminacy, leaving the hard‑deterministic case without a normative account. We model agents as deterministic dynamical systems with bounded knowledge that maintain a probability distribution over hidden variables. By comparing the expected utility of an epistemic‑possibility‑aware policy with that of any collapsed policy that commits to a single deterministic guess, we prove a weak‑dominance theorem: the aware policy never yields lower expected utility and yields strictly higher utility precisely when the collapsed guess is sub‑optimal. Numerical illustrations—(i) a symmetric binary case with zero advantage, (ii) an asymmetric case with a 2.8‑unit advantage, (iii) a Bayesian update case with a 4.2‑unit advantage, and (iv) an equality case confirming the corrected theorem—are derived step‑by‑step from explicitly stated assumptions. The result integrates insights from eight (and, where relevant, eleven) recent works on flow‑aligned cognition, procedural performance metrics, counterfactual knowledge tracing, identifiability limits, counterfactual quantum communication, moral‑reasoning prompting, counterfactual image evaluation, and Cox’s plausibility theorem. The analysis shows that even under hard determinism, maintaining epistemic alternatives is normatively required. Practical implications for AI system design, cognitive‑science interventions, and quantum‑communication engineering are outlined, with a readiness assessment of TRL 2 and a concrete pilot experiment proposed to falsify the claim.",
  "abstract_markdown": "Deterministic physical theories deny genuine alternatives, yet agents must act under incomplete knowledge of hidden causal variables that fix outcomes. Existing decision‑theoretic analyses of counterfactuals presuppose metaphysical indeterminacy, leaving the hard‑deterministic case without a normative account. We model agents as deterministic dynamical systems with bounded knowledge that maintain a probability distribution over hidden variables. By comparing the expected utility of an *epistemic‑possibility‑aware* policy with that of any *collapsed* policy that commits to a single deterministic guess, we prove a **weak‑dominance theorem**: the aware policy never yields lower expected utility and yields strictly higher utility precisely when the collapsed guess is sub‑optimal. Numerical illustrations—(i) a symmetric binary case with zero advantage, (ii) an asymmetric case with a 2.8‑unit advantage, (iii) a Bayesian update case with a 4.2‑unit advantage, and (iv) an equality case confirming the corrected theorem—are derived step‑by‑step from explicitly stated assumptions. The result integrates insights from eight (and, where relevant, eleven) recent works on flow‑aligned cognition, procedural performance metrics, counterfactual knowledge tracing, identifiability limits, counterfactual quantum communication, moral‑reasoning prompting, counterfactual image evaluation, and Cox’s plausibility theorem. The analysis shows that even under hard determinism, maintaining epistemic alternatives is normatively required. Practical implications for AI system design, cognitive‑science interventions, and quantum‑communication engineering are outlined, with a readiness assessment of TRL 2 and a concrete pilot experiment proposed to falsify the claim.",
  "date": "2026-10-20",
  "first_published": "2026-10-20",
  "last_revised": "2026-10-21T06:01:12Z",
  "modified": "2026-10-21T06:01:12Z",
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  "url": "https://papers.qnfo.org/papers/counterfactual-reasoning-as-epistemically-necessary-in-deterministic-agents",
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        "name": "Rowan Brad Quni-Gudzinas",
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    "titles": [
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        "title": "Counterfactual Reasoning as Epistemically Necessary in Deterministic Agents"
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        "description": "Deterministic physical theories deny genuine alternatives, yet agents must act under incomplete knowledge of hidden causal variables that fix outcomes. Existing decision‑theoretic analyses of counterfactuals presuppose metaphysical indeterminacy, leaving the hard‑deterministic case without a normative account. We model agents as deterministic dynamical systems with bounded knowledge that maintain a probability distribution over hidden variables. By comparing the expected utility of an epistemic‑possibility‑aware policy with that of any collapsed policy that commits to a single deterministic guess, we prove a weak‑dominance theorem: the aware policy never yields lower expected utility and yields strictly higher utility precisely when the collapsed guess is sub‑optimal. Numerical illustrations—(i) a symmetric binary case with zero advantage, (ii) an asymmetric case with a 2.8‑unit advantage, (iii) a Bayesian update case with a 4.2‑unit advantage, and (iv) an equality case confirming the corrected theorem—are derived step‑by‑step from explicitly stated assumptions. The result integrates insights from eight (and, where relevant, eleven) recent works on flow‑aligned cognition, procedural performance metrics, counterfactual knowledge tracing, identifiability limits, counterfactual quantum communication, moral‑reasoning prompting, counterfactual image evaluation, and Cox’s plausibility theorem. The analysis shows that even under hard determinism, maintaining epistemic alternatives is normatively required. Practical implications for AI system design, cognitive‑science interventions, and quantum‑communication engineering are outlined, with a readiness assessment of TRL 2 and a concrete pilot experiment proposed to falsify the claim.",
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