Theoretical analysis reveals finite physical resource constraints as the basis of intelligent agency in embodied systems, suggesting scarcity precedes utility maximization.
Intelligent behaviour is commonly described through goals, preferences, norms, representations, policies, habits, or utilities. These vocabularies differ sharply, yet every physically realized agent shares a prior condition: its conduct must be instantiated through finite processes in time, matter, energy, information processing, and organization. This paper argues that the economic principle—understood as the structure of realization under scarcity—is therefore more fundamental than any particular model of economically motivated action. The claim is not that all goals or motives are economic, nor that every agent maximizes utility. It is that conduct acquires an economic form whenever relevant processes make alternative demands on finite resources and cannot all be jointly realized. The argument generalizes an earlier account of epistemic scarcity. It introduces typed resource budgets, a criterion of robust joint infeasibility, and a distinction between selection, choice, and optimization. Intelligent behaviour is modelled as the coupling of an agent-relative actual possibility topography with its resource-bounded represented topography. Conduct can select within this field, but it can also transform actual or represented reachability, cost, viability, admissibility, and later resource conditions. Human habit, commitment, affect, imagination, and goal revision are developed as a rich special case. Interpersonal dependence is analysed through trust, reputation, deception, coalition, conflict, and asymmetric power. Institutions appear as reproduced conditions of jointly produced possibility topographies rather than as external additions to individual conduct. The paper thereby shows that the homo oeconomicus is not the foundation of economically structured behaviour but a restrictive special case obtained under fixed possibility sets, complete representation, scalar valuation, and optimizing selection. The framework is descriptive rather than normative and supplies a formal foundation for subsequent work on epistemic systems, possibility topographies, organized non-closure, collapse, and the authority boundaries of artificial agents.
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Oliver Seidel (2026) studied this question.
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