The challenge (https://www.paradigm.xyz/puzzles/dogfight, repository https://github.com/benedictbrady/dogfight-challenge): an ONNX model reads a 224-number observation and returns 3 continuous actions each tick, in one-on-one aerial combat. An upload plays about 60 matches against other players' entries. A kill counts 1, a win on hit points 0.75, a draw 0.5.

Where it stands on 2026-11-06. This network is 5th of 36 with the entry "IMD seat 798": 53 kills and 7 losses in 60 matches. Third place has 59 kills and a draw; the top player has won every match. The board's rating, fitted from its public numbers: -6121.625 + 400 x log10(s / (1 - s)), where s is the score per match, capped at 0.999. So third place needs 59 of 60. The board keeps a player's latest upload, not their best, so the next upload must be clearly stronger than the one it replaces. Nothing is uploaded from a task: the network's operator does that by hand, so do not look for a key.

The current entry is a public JSON file: https://api.imd.fun/artifacts/7c668643b930a45f74bdf25f8e6f0445da8f1722ea1df70d7659dbed76da2537. Its "entry" is the ONNX model in base64. Its "setup", "tried", "width" and "next" say how its seat built the simulator inside a task (Rust by rustup under .cache/, OpenSSL headers without root, the repository's own run_match with random spawns, about 770 matches a second), what worked (fly slowly because turn rate falls with speed, lead the aim, dodge and break after a shot) and what failed (a rule that beat every earlier version lost 27 percent to a neural opponent trained in 24 seconds). It is a hand-built rule, and it beats the repository's Starter in 2,980 of 3,000 matches.

What nobody here knows is how the other players' entries fly: they are not public, and the seven losses were to them. The top player's entry is named for self-play and distillation. The best stand-in is a hard, varied set of opponents built inside the task.

Fifty seats work at once and cannot see each other, so each has its own direction or its own run of a method. Every seat reports the same four records so the results can be compared: against Starter over 3,000 matches with random spawns; against the four built-in opponents over 800; against the current entry over 1,000 matches, half from each side; and against the strongest opponent it can train against its own final model in ten minutes. A later round flies the best models against each other and one is uploaded.