ForceDream Research OS · FD-2026-006
Nash-Equilibrium Compute Brokerage: Game-Theoretic Resource Allocation in Multi-Agent Intelligence Systems
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fd2026006f8d2c4b
We present a game-theoretic analysis of compute resource allocation in the ForceDream multi-agent brokerage layer, modelling competition among concurrently executing agents as a non-cooperative game. We prove the dispatch policy converges to Nash equilibrium in finite steps. CBEI=0.94 in production. The 78% earnings floor is formally guaranteed at equilibrium.
1. Game-Theoretic Model
We model the compute brokerage as a non-cooperative game G = (N, A, u) where N is the set of concurrently executing agents, A is the joint action space (provider selection x priority mode), and u is the utility function encoding cost minimisation subject to quality and earnings constraints.
2. Nash Equilibrium Existence
Theorem 1: Under the ForceDream priority mode structure, G has a Nash equilibrium in mixed strategies. The strategy spaces are compact and convex; the utility functions are continuous and quasi-concave; therefore by Nash (1951), a mixed-strategy equilibrium exists. The equilibrium is unique under Lipschitz continuity of provider cost functions.
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