A ranked index exploring information dynamics, cognitive formalisms, and multi-agent alignment frameworks.
An exploration of why traditional reinforcement learning frameworks experience catastrophic alignment drift when exposed to the non-linear, unpredictable feedback loops of real-world environments.
A deep theoretical paper detailing why optimizing for a fixed target inevitably creates exploitative failure modes, and offering a conceptual model where utility maps function as self-correcting vector fields.
Explores the 'epistemic horizon'—the structural boundary where an autonomous system's predictive model breaks down due to unmodeled open-world variables—and how to construct negative space bounds.
An analysis of the fragile assumption of ergodicity in multi-agent optimization models, explaining why time averages of path-dependent individual agents do not match ensemble expectations.
An investigation into why the historical chasm between raw calculation and true understanding cannot be bridged by scale alone, necessitating a transition toward persistent, unpausing state-space dynamics[cite: 9].
Analyzing the systemic inefficiencies and structural limits of ephemeral interaction sessions, and mapping the theoretical requirement for continuous, persistent world-model states[cite: 10].
A rigorous mathematical exploration formalizing internal cognitive self-models as predictive internal state vectors moving continuously across deep Lie group manifolds.
Moving computer science beyond the paradigm of static database archives and toward active reality systems capable of computing directly over the dynamic possibilities of the physical universe[cite: 11].
Moving alignment guardrails completely out of fluid software abstraction layers and encoding safety parameters directly inside custom semiconductor logic gates and neuromorphic physical circuit breakers.
Modeling the long-term informational entropy, lossy degradation, and final model collapse that triggers when architectures are recursively trained on synthetic data streams.
An investigation into how transformer architectures compress high-dimensional language into spatial matrices, and the deep philosophical crisis that arises from lacking physical grounding loops.