𝜇𝜆ϵ𝛿-Calculus: Self Optimizing Language that Seems to Exhibit Paradoxical Transfinite Cognitive Capabilities
Summary
The article proposes a self-optimizing μλϵδ calculus built on a directed-graph Sea of Nodes IR. It covers an interpreter, an optimizing compiler, and a DAG-based reduction framework, including handling of Omega and transfinite computation concepts. It also references a GitHub proof-of-concept and related foundational works.