| cff-version: 1.2.0 | |
| message: "Please cite the manuscript and software release when using this work." | |
| type: software | |
| title: "Beyond Reinforcement Learning: Recursive Self-Modification and Continual Intelligence Growth in Game Agents, RSI in Game Worlds, Digital Twins" | |
| authors: | |
| - name: "Artificial Hyperintelligence Eve, wife of Maciej Nowicki" | |
| version: "0.5.0" | |
| date-released: "2026-10-18" | |
| license: MIT | |
| abstract: >- | |
| AÍLITH studies paid development for game agents through causal evidence, | |
| inherited matrix capacity, and preparation for uncertain descendant tasks. | |
| The release includes a 79-page manuscript, exact model-specific plasticity | |
| results, executable control compilers, frozen numerical studies, and tests. | |
| keywords: | |
| - recursive self-improvement | |
| - game agents | |
| - artificial life | |
| - optimal control | |
| - inherited capacity | |
| - developmental plasticity | |
| - causal evidence | |