Ecolistico Digest

Here's a high-density insight extraction: * Mechanism: Breaks the assumption of independent agent learning by introducing a principal that aggregates and redistributes information, shaping agent learning objectives. * Transfer: Principal-agent learning ≈ resource allocation in a distributed sensor network optimizing for global objectives while respecting local constraints and private data. * Constructible Horizon: Build distributed AI systems where a central "governor" optimizes global performance based on aggregated, privacy-preserving agent data. * Antifragility Check: Relies on the principal's ability to accurately model agent behavior and the validity of the conditional moment restrictions, creating a single point of failure.