Foundations of Strategic Computing in AI Systems: OS2x2 Whitepaper (v3.0)

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 Trading Strategy Knowledge (TSK). This document serves as the theoretical and architectural foundation of the OS2x2 platform and the broader category of computed strategy. What’s new in v3.0 introduced the OS2x2 Strategy Knowledge Ecosystem with its first major domain deployments: Personal, Business, Finance, Trading, Learning, Healthcare, Games, and Innovation. Website: https://os2x2.com

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-24
DOI
https://doi.org/10.5281/zenodo.19210540
Primary Topic
Cognitive Science and Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Foundations of Strategic Computing in AI Systems: OS2x2 Whitepaper (v3.0)

Zenodo (CERN European Organization for Nuclear Research)
Cognitive Science and Mapping
article

Foundations of Strategic Computing in AI Systems: OS2x2 Whitepaper (v3.0)

article en

Abstract

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 Trading Strategy Knowledge (TSK). This document serves as the theoretical and architectural foundation of the OS2x2 platform and the broader category of computed strategy. What’s new in v3.0 introduced the OS2x2 Strategy Knowledge Ecosystem with its first major domain deployments: Personal, Business, Finance, Trading, Learning, Healthcare, Games, and Innovation. Website: https://os2x2.com

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 12%
Cognitive Science and Mapping
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