Foundations of Strategic Computing in AI Systems: OS2x2 Whitepaper (v2.9)

This whitepaper introduces Strategy Knowledge Science (SKS) as a formal framework for representing strategic environments as computable state-spaces. It presents the OS2x2 architecture as a strategic computing system for positioning, feasibility analysis, trajectory computation, verified strategic decision-making, continuous strategic memory, and strategic learning over time. The paper defines the core layers of strategic computation — Strategic Geometry, Strategic Algebra, Strategic Mechanics, Strategic Topology, and Strategic Field Theory — and shows how they are translated into an applied computational architecture for deployment, runtime computation, graph-based strategic memory, and validation. It also introduces the Strategy Knowledge Model (SKM) as a new class of strategic-native artificial intelligence aligned with strategic state-spaces, constraints, and trajectories rather than linguistic plausibility alone, and extends the framework into financial markets through Strategy Knowledge Trading (SKT). This document serves as the theoretical and architectural foundation of the OS2x2 platform and the broader category of computed strategy. What’s new in v2.9 added Strategy Knowledge Trading (SKT) as the formal extension of SKS into financial markets expanded the framework to market state-spaces, cross-asset field dynamics, and strategic backtesting in trading contexts Website: https://os2x2.com