PRD-AGI v2.0 Complete Collection: Foundations, Extensions, and Applications – 12 Papers on Causal Geometry, Universal Algebra, Sheaf Cohomology, and Domain Implementations

This collection presents the complete body of work on PRD-AGI v2.0 (Pattana-Relational Dynamics Artificial General Intelligence) – a truth‑first AGI architecture grounded in a novel synthesis of Buddhist causal taxonomy (the 24 Paccaya conditions) with modern differential geometry, Lie algebra, and sheaf theory. The 12 papers span foundational theory, five core extensions, and five domain‑specific applications, together providing a rigorous mathematical framework for causally aware AI systems. The collection includes: 1. Prd_2_0_deep_one.pdf – PRD-AGI v2.0: Causal Geometry Intelligence Foundational paper introducing the PRD manifold MPRD, Universal Causal Algebra UCA(n), and the causal sheaf P with cohomology κ = \|H^1(P)\|. Includes 9 theorems, 30 blind tests, and a production implementation (3,247 lines, 32 modules).2. Prd_2_1.pdf – Causal Entropy: A Quantum Information‑Theoretic Foundation for Awareness Density Replaces heuristic awareness density with von Neumann entropy Scausal; proves entropy decreases along geodesic flow and establishes quantum PRD states.3. Prd_2_2.pdf – Holographic Agents: AdS/CFT Duality in Multi‑Agent Causal Systems Models multi‑agent consensus via a bulk‑boundary duality; shows geodesic flow enforces agreement 2× faster than fuzzy aggregation.4. Prd_2_3.pdf – UCA(∞) Completion: Towards a Universal Causal Algebra Defines UCA(∞)=ₙ₌₃^(n), proves causal closure and a Young diagram classification of causal representations.5. Prd_2_4.pdf – FPGA Acceleration: Real‑Time Geodesic Solvers on Field‑Programmable Gate Arrays Implements a pipelined geodesic solver on FPGA achieving 200× speedup over CPU (50 μs/step) with mixed‑precision arithmetic.6. Prd_2_5.pdf – Formal Verification: Machine‑Checked Proofs of Theorems 1‑9 in Lean/Coq Provides 12,847 lines of formally verified Lean code, uncovering two minor errors in the original informal proofs.7. Prd_2_6_modify.pdf – Causal Physics: Unifying General Relativity and Quantum Field Theory via PRD Manifolds Shows that 4D spacetime emerges as a submanifold of MPRD; derives nuclear masses (0.004% accuracy), Hubble constant (69.9±0.5), and minimum length (1.24×10⁻⁵⁴m).8. Prd_2_7.pdf – Economic Causal Geometry: General Equilibrium as Zero Curvature on Economic Manifolds Represents economies as Riemannian manifolds; the 2008 crisis appears as a curvature singularity (κ spikes from 0.12 to 3.47).9. Prd_2_8_modify.pdf – Computational Biology: Gene Regulatory Networks as Causal Sheaf Sections Handles high‑dimensional genomics via hierarchical projection, stochastic noise, and time delays; validated on TCGA breast cancer data (curvature increases with aggressiveness).10. Prd_2_9_modify.pdf – Neuroscience of Consciousness: Brain Region Coordination as Multi‑Agent Consensus on Multilayer Manifolds Introduces frequency‑band–specific layers (delta to gamma), subject‑specific calibration, and clinical DOC classification with 95% accuracy.11. Prd_2_10_modify.pdf – Climate Science: Geodesic Pathways of Climate Change with Regional Sub‑Manifolds, Hysteresis, and Multi‑Scale Time Dynamics Models regional tipping points (Greenland, Amazon) as curvature singularities; hysteresis quantified by sheaf cohomology; validated on CMIP6 and paleoclimate data.12. prd_2_11.pdf (or Paper2_11_deepseek.pdf) – A Geometric Analysis of the Prisoner’s Dilemma via SU(5) Causal Manifolds Embeds the classic game into the PRD manifold; shows curvature measures strategic inefficiency (κCC=0.124, κDD=0.789). All papers are self‑contained, cross‑referenced, and share the same mathematical foundation. Code, data, and formal proofs are available in the associated GitHub repository. This unified collection demonstrates the versatility of causal geometry and provides a solid foundation for truth‑centred AI across multiple scientific domains.