This collection establishes a framework measuring sentience through adaptive control capacity, suggesting implications for understanding diverse organisms.
This collection presents a unified framework for operationalizing and comparing sentience across organisms as adaptive control capacity (ACC). The framework measures how effectively an organism's control system uses available information to steer toward organism-optimal states across environmental variation within finite time. The collection comprises four complementary papers: Paper 1: Comparing Organism "Sentience" as Adaptive Control Capacity (2a84b82e-c974) provides the interpretation-agnostic mathematical foundation. It defines normalized regret—shortfall from organism-specific optima—as the core performance measure, enabling rigorous comparison across radically different morphologies, timescales, and sensory modalities without assuming shared state spaces or behavioral repertoires. Three comparison relations are developed: expected regret, worst-case robustness, and stochastic dominance. Paper 2: Why Sentience (97b3cbd2-b036) argues that ACC operationalizes sentience—welfare-grounding subjectivity—more directly than intelligence. The framework's organism-relative normalization and evaluative structure align with philosophical treatments of phenomenal consciousness and welfare subjectivity, measuring the for-the-organism dimension rather than cognitive power or competence. Paper 3: Grounding Adaptive Control Capacity in a Theoretical Framework (44f4b253-d070) situates ACC within established formal traditions: cybernetics, sequential decision-making under partial observability, information-theoretic control, bounded rationality, and distributional robustness. It transforms the abstract regret functional into a capacity envelope with explicit constraint semantics and principled comparison operators. Paper 4: Sentience Within the Varied Kingdoms of Life Beyond Animals (e26bb8d1-6572) demonstrates that the functional signatures ACC formalizes—evaluated choice, distributional sensitivity, experience-dependent improvement, and constraint-sensitive tradeoffs—appear empirically across plants, slime molds, and single cells. The framework renders scattered cross-kingdom evidence commensurable and supports quantitative comparison. Together, these papers provide: (1) rigorous mathematical specification, (2) philosophical grounding for the "sentience" interpretation, (3) theoretical embedding in decision theory and control, and (4) empirical validation across diverse substrates. Each paper is self-contained but gains context from the others. This project was developed with the assistance of contemporary AI-based tools that support rapid review of existing sources, engagement with well-established theoretical frameworks, and efficient construction and revision of integrated results. The author assumes full responsibility for the content, structure, and conclusions presented. Still, the work should be considerd an early draft stage and needs review by external reviewers.
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Daniel S. Goldman (2026) studied this question.
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