Independent Researcher · Ouroboros Project
I study Wisdom Science: how AI agents, embodied systems, and decision architectures improve through feedback, perturbation, evidence gates, recovery, and long-horizon experience.
Research Program
Most evaluations ask whether an agent succeeds on the first attempt. My work asks a different question: after failure, feedback, or environmental shift, does the system become more reliable, more bounded, and more capable of choosing the right next action?
The portfolio formalizes this question across cognitive agents, embodied benchmarks, world-model evidence, social calibration, cognitive immunity, and robust perception under adverse conditions.
Metrics and protocols for learning from repeated exposure, failure modes, perturbations, and recovery.
WB-E evaluates physical agents beyond first-attempt success, emphasizing recovery, provenance, and bounded action.
Failure is treated as an antigen: a reusable signal for improved reasoning, safety, and decision hygiene.
Agents must reason about how their actions change the environment that will later evaluate them.
Art Direction
The public layer is designed as an editorial research space: quiet, precise, warm enough to enter, and strong enough to be remembered. The goal is not spectacle. The goal is trust with taste.
Public Archive
Public preprints may contain author identity. Double-blind conference submissions use separate anonymous packages.
Systems Layer
The engineering layer organizes evidence trails, failure logs, workflow memory, social calibration, cognitive immunity, and closed-loop teaching into a practical system for research, operations, and reliable agent design.
Position
The next route is not only larger models. It is architecture, feedback, evidence, recovery, body-like subsystems, and the discipline to know when not to act.
This is a research archive, a systems map, and a public instrument panel for work that must remain falsifiable.
Contact
Independent Researcher, Ouroboros Project