A General Equilibrium Theory of Orchestrated AI Agent Systems
arXiv:2602.21255v1 Announce Type: cross Abstract: We establish a general equilibrium theory for systems of large language model (LLM) agents operating under centralized orchestration. The framework is a production economy in the sense of Arrow-Debreu (1954), extended to infinite-dimensional commodity spaces following Bewley (1972). Each LLM agent is modeled as a firm whose production set Y a $\subset$ H = L 2 ([0, T ], R R ) represents the feasible metric trajectories determined by its frozen model weights. The orchestrator is the consumer, choosing a routing policy over the agent DAG to maximize system welfare subject to a budget constraint evaluated at functional prices p $\in$ H A . These prices-elements of the Hilbert dual of the commodity space-assign a shadow value to each metric of each agent at each instant. We prove, via Brouwer's theorem applied to a finitedimensional approximation V K $\subset$ H, that every such economy admits at least one general equilibrium (p * , y * ,
arXiv:2602.21255v1 Announce Type: cross Abstract: We establish a general equilibrium theory for systems of large language model (LLM) agents operating under centralized orchestration. The framework is a production economy in the sense of Arrow-Debreu (1954), extended to infinite-dimensional commodity spaces following Bewley (1972). Each LLM agent is modeled as a firm whose production set Y a $\subset$ H = L 2 ([0, T ], R R ) represents the feasible metric trajectories determined by its frozen model weights. The orchestrator is the consumer, choosing a routing policy over the agent DAG to maximize system welfare subject to a budget constraint evaluated at functional prices p $\in$ H A . These prices-elements of the Hilbert dual of the commodity space-assign a shadow value to each metric of each agent at each instant. We prove, via Brouwer's theorem applied to a finitedimensional approximation V K $\subset$ H, that every such economy admits at least one general equilibrium (p , y , $\pi$ * ). A functional Walras' law holds as a theorem: the value of functional excess demand is zero for all prices, as a consequence of the consumer's budget constraint-not by construction. We further establish Pareto optimality (First Welfare Theorem), decentralizability of Pareto optima (Second Welfare Theorem), and uniqueness with geometric convergence under a contraction condition (Banach). The orchestration dynamics constitute a Walrasian t{\^a}tonnement that converges globally under the contraction condition, unlike classical t{\^a}tonnement (Scarf, 1960). The framework admits a DSGE interpretation with SLO parameters as policy rates.
Executive Summary
The article presents a groundbreaking general equilibrium theory for systems of large language model (LLM) agents under centralized orchestration. It models each LLM agent as a firm within a production economy framework, extending the Arrow-Debreu model to infinite-dimensional commodity spaces. The orchestrator, acting as the consumer, maximizes system welfare through routing policies over agent DAGs, subject to budget constraints evaluated at functional prices. The authors prove the existence of general equilibrium using Brouwer's theorem and establish key economic theorems such as Walras' law, Pareto optimality, and the decentralizability of Pareto optima. The framework also introduces a dynamic Walrasian tâtonnement that converges globally under certain conditions, offering a novel approach to understanding AI agent systems within a DSGE interpretation.
Key Points
- ▸ Introduction of a general equilibrium theory for LLM agent systems under centralized orchestration.
- ▸ Modeling LLM agents as firms within an extended Arrow-Debreu production economy framework.
- ▸ Proof of the existence of general equilibrium using Brouwer's theorem.
- ▸ Establishment of key economic theorems including Walras' law, Pareto optimality, and decentralizability of Pareto optima.
- ▸ Introduction of a dynamic Walrasian tâtonnement with global convergence under contraction conditions.
Merits
Innovative Framework
The article introduces a novel and rigorous framework for analyzing AI agent systems using general equilibrium theory, extending classical economic models to infinite-dimensional spaces.
Mathematical Rigor
The use of Brouwer's theorem and other advanced mathematical tools ensures the robustness and validity of the theoretical constructs presented.
Practical Implications
The framework provides a foundation for understanding the economic dynamics of AI agent systems, which can have significant implications for policy and practical applications.
Demerits
Complexity
The high level of mathematical sophistication may make the framework inaccessible to non-specialists, limiting its immediate practical applicability.
Assumptions and Conditions
The theory relies on specific assumptions and conditions, such as the contraction condition for global convergence, which may not hold in all real-world scenarios.
Empirical Validation
The article lacks empirical validation, which is crucial for assessing the practical relevance and robustness of the theoretical framework.
Expert Commentary
The article represents a significant advancement in the intersection of economics and AI, providing a rigorous theoretical foundation for understanding the dynamics of AI agent systems. The extension of classical economic models to infinite-dimensional commodity spaces is a notable contribution, offering a novel perspective on the orchestration of AI agents. The proof of general equilibrium and the establishment of key economic theorems within this framework are particularly impressive. However, the complexity of the mathematical constructs may limit the immediate practical applicability of the theory. Future research should focus on empirical validation and the relaxation of assumptions to enhance the framework's robustness and relevance. The implications for policy and practical applications are substantial, potentially guiding the development of more efficient and ethically sound AI systems.
Recommendations
- ✓ Conduct empirical studies to validate the theoretical framework and assess its practical relevance.
- ✓ Explore the relaxation of assumptions, such as the contraction condition, to broaden the applicability of the theory.