code wiki / _hdl_build / nx_genetic_algorithm_gate.nx
nx_genetic_algorithm_gate.nx source
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1import "nx_gate_gn.nx"
2import "nx_gate_base.nx"
3// nx_genetic_algorithm_gate.nx -- the full GENETIC ALGORITHM (Holland 1975): population + tournament selection +
4// single-point crossover + bit-flip mutation + elitism, evolving to the optimum (operator: build the full mechanistic /
5// non-transformer AI foundation -- GA/MOEA/metaheuristics before leaning on LLMs). The ecosystem had only a (1+lambda)
6// evolution strategy (nx_evo_synth); this is the canonical population GA with CROSSOVER, the #1 evolutionary-computation
7// gap. Stochastic but REPRODUCIBLE via a sovereign LCG PRNG (seeded) -> 2x-deterministic. Demo: OneMax (maximize the
8// number of 1-bits in an L-bit genome; optimum = all ones, fitness L) -- the canonical GA benchmark. No LLM.
9// T0 POPULATION: P random L-bit genomes seeded by the sovereign LCG.
10// T1 SELECTION: tournament picks the fitter of two random genomes (selection pressure).
11// T2 CROSSOVER: single-point recombination combines two parents' bits.
12// T3 MUTATION: bit-flip introduces variation.
13// T4 EVOLUTION: best fitness rises generation over generation and REACHES the optimum (all ones, fitness L).
14// T5 = a full GA (population/selection/crossover/mutation/elitism) solved OneMax, mechanistic, reproducible, no LLM.
15// license_tier: ORIGINAL
16import "nx_syscalls.nx"
17
18// sovereign LCG PRNG (glibc constants) -- deterministic, seeded -> reproducible stochasticity.
19func grow(name: *u8, ok: i64) -> i64 { if ok==1 { gw(" PASS " as *u8) } else { gw(" FAIL " as *u8) } gw(name); gw("
20" as *u8); return ok }
21func rng(st: *i64) -> i64 { st[0]=((st[0]*1103515245)+12345) & 0x7FFFFFFF; return st[0] }
22func rng_n(st: *i64, n: i64) -> i64 { return rng(st)%n }
23func popcount(x: i64, L: i64) -> i64 { var c: i64=0; var i: i64=0; while i<L { if ((x>>i)&1)==1 { c=c+1 } i=i+1 } return c }
24func crossover(a: i64, b: i64, L: i64, st: *i64) -> i64 { let pt: i64=rng_n(st,L); let lowmask: i64=(1<<pt)-1; let full: i64=(1<<L)-1; return (a & lowmask) | (b & (full - lowmask)) }
25func mutate(x: i64, L: i64, st: *i64) -> i64 { if rng_n(st,100)<25 { let bit: i64=rng_n(st,L); return (x ^ (1<<bit)) & ((1<<L)-1) } return x }
26
27func main() -> i64 {
28 gw("=== nx_genetic_algorithm_gate: the full Genetic Algorithm (population+selection+crossover+mutation), no LLM ===\n" as *u8)
29 var pass: i64=0; var total: i64=0
30 let P: i64=24; let L: i64=14; let MAXGEN: i64=300
31 let st: *i64=sys_mmap(16) as *i64; st[0]=12345 // fixed seed -> reproducible
32 let pop: *i64=sys_mmap(256) as *i64; let fit: *i64=sys_mmap(256) as *i64; let np: *i64=sys_mmap(256) as *i64
33
34 // T0 init population.
35 var i: i64=0; while i<P { pop[i]=rng_n(st, 1<<L); i=i+1 }
36 total=total+1; pass=pass+1
37 gw(" [PASS] T0 POPULATION: " as *u8); gn(P); gw(" random " as *u8); gn(L); gw("-bit genomes (sovereign LCG seeded) -- e.g. genome0 has " as *u8); gn(popcount(pop[0],L)); gw(" ones\n" as *u8)
38
39 // T1 selection: tournament.
40 let g_a: i64=(1<<L)-1; let g_b: i64=0 // all-ones vs all-zeros
41 var winner: i64=g_b; if popcount(g_a,L)>=popcount(g_b,L) { winner=g_a }
42 total=total+1; if winner==g_a { pass=pass+1; gw(" [PASS] " as *u8) } else { gw(" [FAIL] " as *u8) }
43 gw("T1 SELECTION: tournament(all-ones[fit " as *u8); gn(popcount(g_a,L)); gw("], all-zeros[fit 0]) -> picks the fitter (selection pressure)\n" as *u8)
44
45 // T2 crossover.
46 let child: i64=crossover((1<<L)-1, 0, L, st)
47 total=total+1; pass=pass+1
48 gw(" [PASS] T2 CROSSOVER: single-point(all-ones, all-zeros) -> child with " as *u8); gn(popcount(child,L)); gw(" ones (recombined parents)\n" as *u8)
49
50 // T3 mutation.
51 var muts: i64=0; i=0; while i<200 { let before: i64=0; let after: i64=mutate(before,L,st); if after!=before { muts=muts+1 } i=i+1 }
52 total=total+1; if muts>0 { pass=pass+1; gw(" [PASS] " as *u8) } else { gw(" [FAIL] " as *u8) }
53 gw("T3 MUTATION: bit-flip fired " as *u8); gn(muts); gw("/200 times (introduces variation)\n" as *u8)
54
55 // T4 EVOLUTION: run the GA.
56 var gen: i64=0; var best: i64=0; var bestgen: i64=0-1; var firstbest: i64=0
57 while gen<MAXGEN {
58 // fitness + track best (elitism index)
59 var bi: i64=0; i=0; while i<P { fit[i]=popcount(pop[i],L); if fit[i]>fit[bi] { bi=i } i=i+1 }
60 if fit[bi]>best { best=fit[bi] }
61 if gen==0 { firstbest=fit[bi] }
62 if fit[bi]==L { bestgen=gen; gen=MAXGEN } else {
63 // new generation: elitism keeps the best, rest via tournament+crossover+mutation
64 np[0]=pop[bi]; var c: i64=1
65 while c<P {
66 let a1: i64=rng_n(st,P); let a2: i64=rng_n(st,P); var p1: i64=pop[a1]; if fit[a2]>fit[a1] { p1=pop[a2] }
67 let b1: i64=rng_n(st,P); let b2: i64=rng_n(st,P); var p2: i64=pop[b1]; if fit[b2]>fit[b1] { p2=pop[b2] }
68 np[c]=mutate(crossover(p1,p2,L,st), L, st); c=c+1
69 }
70 i=0; while i<P { pop[i]=np[i]; i=i+1 }
71 gen=gen+1
72 }
73 }
74 total=total+1; if best==L { if bestgen>=0 { pass=pass+1; gw(" [PASS] " as *u8) } else { gw(" [FAIL] " as *u8) } } else { gw(" [FAIL] " as *u8) }
75 gw("T4 EVOLUTION: best fitness gen0=" as *u8); gn(firstbest); gw(" -> REACHED optimum " as *u8); gn(best); gw("/" as *u8); gn(L); gw(" (all ones) at generation " as *u8); gn(bestgen); gw("\n" as *u8)
76
77 // T5.
78 total=total+1; if best==L { pass=pass+1; gw(" [PASS] " as *u8) } else { gw(" [FAIL] " as *u8) }
79 gw("T5 GENETIC ALGORITHM: population/tournament-selection/crossover/mutation/elitism solved OneMax to the optimum, no LLM\n" as *u8)
80
81 gw("\n GENETIC ALGORITHM (Holland): a population of genomes evolved by SELECTION (tournament) + CROSSOVER (single-point) + MUTATION\n" as *u8)
82 gw(" (bit-flip) + ELITISM reached the OneMax optimum (all ones). Stochastic but REPRODUCIBLE (sovereign LCG, fixed seed). This is\n" as *u8)
83 gw(" the canonical population GA with crossover that the ecosystem lacked (only a (1+lambda) ES existed). Foundation for the full\n" as *u8)
84 gw(" evolutionary-computation stack: next MOEA/Pareto (multi-objective) + metaheuristics (annealing/tabu/ACO). All mechanistic, no LLM.\n" as *u8)
85 gw("GENETIC-ALGORITHM verdict=" as *u8)
86 if pass==total { gw("GREEN passes=" as *u8); gn(pass); gw("/" as *u8); gn(total); gw(" -- full GA solved OneMax, reproducible, no LLM\n" as *u8); sys_exit(0); return 0 }
87 gw("RED passes=" as *u8); gn(pass); gw("/" as *u8); gn(total); gw("\n" as *u8); sys_exit(1); return 1
88}