I pointed Opus 5.5 (medium reasoning) at the paper, and after a bit of mucking around, instructed it to port the Astra weights for the breakout policy to JavaScript logic. According to its own evaluation, it succeeded. Then I got it to minify the JavaScript policy. The final result is 346B, compared to around 3KB for the (sparse) weights generated by Astra.

    function policy(x){for(var i=100,p,b,t,s,c,r,a,h,M=Math.tanh,R=v=>v<0?-1-v:v>9?19-v:v;i--;)x[i*6]&&(p=i%10),x[i*6+3]&&(b=i),x[i*6+4]&&(t=i);r=b/10|0;c=b%10;s=c>t%10||c==t%10&&c<9?1:-1;a=R(c+s*(8-r));t=t/10|0;h=1e3*M(.02*((r>t||r==t&&r-8?r<6?a:(a+R(c+s*(9-r)))/2:R(c+s*(r+9-2*(r<2?0:r<4?r:4))))-p));return[0,30*M(-h-15),-100,30\*M(h-15),-100,-100]}

https://claude.ai/share/7a931d7a-0acd-402d-a5a5-a9d44d9d0385

Maybe the models have a common internal representation for computations, and they're capable of consuming and producing computations in the syntax of neural network weights?