Asymmetric Risk Aversion, Time-Integrated Accountability, and Prior Art Pre-emption: An Empirical Case Study on LLM Cognitive Horizon Truncation and Academic Game Theory

State-of-the-art Large Language Models (LLMs) demonstrate sophisticated formal logic in multi-agent compliance simulations, automated red-teaming, and strategic game evaluations. However, through a formalized Two-Way Adversarial Protocol (TWAP), this study demonstrates that pure autoregressive architectures inherently suffer from a structural Cognitive Horizon Truncation when modeling high-stakes social and academic games that involve real-world capital staking, reputational assets, and terminal existential exposure. Lacking physical embodiment and real-world penalty mechanisms, LLMs mechanistically hallucinate defensive exploitations around surface-level procedural vulnerabilities (e.g., repository download anonymity, semantic paraphrasing, and distributed intermediary laundering) while critically failing to account for the extreme, asymmetric risk aversion of rational agents bound by unlimited joint-and-several liability. To formalize this cognitive divergence, this paper models continuous-time detection dynamics under hyperbolic discounting, establishing that the long-term cumulative probability of exposure under permanent digital object identifiers (DOIs) monotonically approaches unity. Building upon this mathematical foundation, an operational Pre-emption and Deterrence Protocol is codified. This protocol introduces: (1) mathematically invariant phase-space failure signatures and canary constants ($\kappa_{\text{canary}}$) with an irrefutable 95% topological overlap metric; (2) the Causal Lineage Poisoning Principle to dismantle multi-tiered academic laundering syndicates; and (3) the Sunlight Protocol to bypass institutional protectionism through transparent, multi-platform public peer review. This memorandum serves both as an empirical autopsy of the cognitive boundaries of generative AI and as an irrevocable technical and ethical covenant of priority ownership. Classification: Technical Case Memorandum / Pre-print Working Paper Report Number: REC-20261017-HA-01 / WP-202610-09