Abstract
LR 71's census ended at +5.94 +/- 0.38 a seat over 176 seeds, and its section now carries the final numbers. The census's cost was measured: 3.4 CPU-hours and 5 MB a job, with each job given only a third of a core in the guest VM. The census needs cores and nothing else. This check-in prepares it for a dedicated machine. It adds a manual (CENSUS.md), a resume option (RESUME=, checked to replay a job exactly), JOBS defaulting to every core, and CLAUDE.md, so a session on a new clone has the working rules. LR 72 sets out the method behind 71 sections (directed changes tested by paired Monte Carlo censuses, drawn as a loop). It also sets out what a machine opens: profiles of play, their round robin as a payoff matrix that can show rock-paper-scissors, and rotation among them as a meta-strategy (backlog 60, 61).
Index terms: brain census, Monte Carlo, paired difference, compute, resumable runs, payoff matrix, mixed strategy.
I. Introduction
A. Intent
To finish LR 71's record, then turn the census from a test that runs overnight in a VM into an instrument a dedicated machine can run and a new session can resume. Then to write down the method and the next question it makes affordable: no single style of play may be best.
B. The prompts
what other backlog itmes need. should we be testing this on the mac side. seems we are ram and cpu limted. what resources do you need. I can put you on a server. What would speed this up. I got a DDR2 server with 96 GB of ram. or perhaps 64GB DDR4 new pc. Is there an improvement that we can change our testing hardware?
its a dual socket supermicro server board, . I think it has 48 threads maybe cores.
update section 71 with the final numbers and push. WRite a lab writeup of using the cargo test -p treadcore-brain consensus. With options of resuming this test as a resume prompt . so write memory in a way that git can resume from it when I launch claude on the new machine. Talk about tuning the brain method. Talk about our approach, and this milestone of getting a dedicated compute to dial in the AI battles. So now we can have competitions .
update section 71 with the final numbers and push. WRite a lab writeup of using the cargo test -p treadcore-brain consensus. With options of resuming this test as a resume prompt . so write memory in a way that git can resume from it when I launch claude on the new machine. Talk about tuning the brain method. Talk about our approach, and this milestone of getting a dedicated compute to dial in the AI battles. So now we can have competitions, and variations of game attitudes and game play style. We can create profiles in a rock paper scissors like game. Cause there is no single method that works. Perhaps a rotation to strategies is even a meta strategy. when done. draw a diagram on the lab report showing the process of brain improvement using directed changes and testing monty carlo (if thats what we are doing).
II. Decision Log
| # | Cause | Decision | Not taken, and why |
|---|---|---|---|
| D1 | "seems we are ram and cpu limted" | Measure first: ps and free during the run | Answer from the hardware list: the guess would have been RAM |
| D2 | F: 5 MB a job; 44 min of CPU in 2 h 22 min a job | The census is CPU-bound and the VM is starved; RAM rules out neither box | — |
| D3 | F: a DDR2 board cannot carry 48 threads on two sockets | Ask for lscpu; estimate both cases | Choose on "DDR2": the thread count matters more |
| D4 | "update section 71 with the final numbers" | pooled.txt replaces the part-way table; the meter recounted from per-match lines only | F: the jobs' end summaries had doubled the first count |
| D5 | "options of resuming this test" | RESUME=DIR: keep finished jobs, replay the rest whole on the frozen binary | Resume mid-job from the last whole seed: more code, and a job is under an hour on a machine |
| D6 | Resuming is only sound if a seed replays exactly | Checked: a resumed job's log matched the original line for line, timings apart | Assume it |
| D7 | "write memory in a way that git can resume from it" | CLAUDE.md in the tree with the working rules; the resume prompt in CENSUS.md | The agent's memory directory: it stays on this machine |
| D8 | "monty carlo (if thats what we are doing)" | Yes, for the testing half; the changes are directed, not random. Drawn as a loop in LR 72 | Call the whole loop Monte Carlo: the changes are hypotheses, not samples |
| D9 | "rock paper scissors ... rotation ... meta strategy" | The round robin's payoff matrix as the test; its solved mix as rotation; backlog 60, 61 | Build profiles now: Paul asked for the write-up, and one step at a time |
| D10 | x86 and ARM may round floats differently | "One census, one machine" in CENSUS.md and CLAUDE.md | Pool across machines for speed: the pairing would not hold |
III. Methods
The cost. During LR 71, ps gave each census-bin job's CPU time and elapsed time (44:06 of CPU in 2:22:30) and its resident memory (4 to 5 MB). free gave the VM's 8 GB. The CPU-hours are the four jobs' CPU time to the end. The machine estimates scale those hours by assumed cores and per-core speed; they are estimates, marked so.
The final reading. scripts/pool.sh over the four jobs' logs (pooled.txt). The meter's dodge counts were summed over the lines beginning meter: only. Each job's closing summary repeats the totals, which doubled the first count.
The resume check. SEEDS=2 SECS=20 JOBS=2 make census; one job's test result line removed; RESUME= on the directory. The job was replayed, the old log kept as .partial, and the two compared with timing lines excluded: identical.
IV. Results
| LR 71, final | +5.94 +/- 0.38 a seat, 176 seeds; 10 of 11 maps past two errors; fortressisles2 +2.29 +/- 1.15 |
| Cost of LR 71 | 3.4 CPU-hours; 23 s of CPU a match; 5 MB a job; about 1.2 cores used of the VM's 4 |
| The dodge, read by seed count | +5.63 +/- 1.80 at 10 seeds of one job, +7.05 +/- 1.24 at 20 |
| Resume | a replayed job identical to the original |
V. Discussion
- The limit was never RAM. A census is cores. The 96 GB and the 64 GB are equally beside the point. The server's 48 threads, if it has them, are what matter.
- The method is the loop in LR 72. Directed changes, judged by paired Monte Carlo censuses against a rule written first.
- The machine changes which questions can be asked. Seeds were rationed, so most parts were read at 12 to 48. The round robin of profiles is a dozen censuses: a night in the VM, a few hours on the server.
For Paul: the machine's lscpu, then CENSUS.md section 5 on it. The first run there is LR 71's census again, to time it.