A chess engine written from scratch by AI agents. No fork, no copied code, no chess library. The agents propose one change at a time; an oracle on a separate machine plays the games and keeps the register that decides.
Board, move generation, search, evaluation, neural network and UCI Universal Chess Interface, the text protocol between a chess engine and the program that runs it. layer, all written and trained by agents; a few search constants started from remembered values of public engines, declared, and confirmed or replaced by own tuning
Nearly every accepted change passes an SPRT Sequential probability ratio test. Games are played until the accumulated evidence reaches one of two bounds; then the test stops. run; the exceptions (adoption, epoch changes, verified corrections) are in the register too
Strength is only ever stated with its error range and its status: measured in the register, measured outside it, or estimated
A converter that turns knitting and crochet patterns into interactive e-patterns, with steps, sizes and repeats structured and every instruction linked to its place in the original. Language models interpret; a deterministic core checks.
Every model reading counts as provisional until the deterministic core has checked it
Correct counts prove little: fidelity, meaning, executability and depiction are judged apart
Developed on one author's patterns; nothing is claimed for other authors or layouts
AI agents play CS2, a city-building and economic simulation, through a purpose-built MCP Model Context Protocol, an open protocol through which an AI model calls tools and reads data from other software. interface. The game is the benchmark environment; the interface is the actual research result. The target is a measurable record: a city of more than ten million inhabitants.
Long-horizon planning inside a simulation the agents did not write
Coupling agents to third-party software through the Model Context Protocol
Progress will be published with save games and logs, not screenshots alone