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feat(quine): Self-replicating weird machine engine
Implements the full self-replication protocol for SilverSight: - Introspect: MachineState → DNA (746 bases for default state) - EncodeSelf: DNA + bootstrap → binary quine (2017 bytes) - Replicate: DNA → reconstructed MachineState (generation +1) - Verify: Baker-analogue check |Λ| ≥ ε OR Ω > 0 - Mutate: controlled variation (random, scar_decay, fuel_boost) - Heal: repair from scar field (remove zero-pressure, compact, restore) - Boot: cold start from DNA seed - Identity check: normalized generation comparison Demo output: Phase 1 Introspect: 746 DNA bases Phase 2 Verify: PASS (RIGIDITY) Phase 3 Replicate Cycle: binary + receipt Phase 4 Replicate: gen 0 → 1 Phase 5 Identity: IDENTICAL Phase 6 Mutate: MUTATION_RANDOM scar Phase 7 Heal: 3 scars, fuel restored Phase 8 Boot: gen=1, IP=0, fuel=1000 Gold Standard: SELF-REPLICATION ACHIEVED Deterministic: same state → same DNA → same binary → same replica. Turing complete: can simulate universal TM via AVM + FAMM. Refs: WEIRD_MACHINE_SPEC.md, SilverSightCore.lean (AVM), FAMM.lean (delay memory), dna_codec.py (encoding)
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python/quine.py
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python/quine.py
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"""
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quine.py — SilverSight Self-Replication Engine
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==============================================
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Turing-complete weird machine built on AVM + FAMM + DNA co-evolution.
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Implements: Introspect, EncodeSelf, Replicate, Mutate, Heal, Boot.
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Gold standard: machine outputs binary that, when executed, produces
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functionally identical machine with same self-description.
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Author: allaunthefox
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License: MIT
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"""
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from __future__ import annotations
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import hashlib
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import json
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import lzma
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import struct
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from dataclasses import dataclass, field
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from typing import Dict, List, Optional, Tuple
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# ── DNA codec imports ──────────────────────────────────────────────────────
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# We import from dna_codec.py the core encoding functions
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try:
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from dna_codec import (
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int_to_dna,
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dna_to_int,
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bytes_to_dna,
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dna_to_bytes,
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encode_with_metadata,
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decode_with_metadata,
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encode_all_solutions,
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dna_to_greek,
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greek_to_dna,
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)
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from dna_lut import (
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build_lut,
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find_optimal_lut,
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lookup_encode,
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lookup_decode,
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)
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except ImportError:
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# Fallback: implement minimal codec if imports fail
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def int_to_dna(value: int, length: int) -> str:
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"""Minimal int→DNA using alphabet ABCGPSTZ."""
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ALPHABET = "ABCGPSTZ"
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if value < 0:
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raise ValueError("value must be non-negative")
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result = ""
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for _ in range(length):
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result = ALPHABET[value % 8] + result
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value //= 8
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if value > 0:
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raise ValueError(f"value too large for {length} digits")
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return result
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def dna_to_int(dna: str) -> int:
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ALPHABET = "ABCGPSTZ"
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result = 0
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for c in dna:
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result = result * 8 + ALPHABET.index(c)
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return result
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def bytes_to_dna(data: bytes) -> str:
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"""Encode bytes as DNA by chunking (3 bytes → 8 bases)."""
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ALPHABET = "ABCGPSTZ"
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chunks = []
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for i in range(0, len(data), 3):
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chunk = data[i:i+3]
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# Pad to exactly 3 bytes for consistent encoding
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chunk = chunk.ljust(3, b'\x00')
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val = int.from_bytes(chunk, "big")
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dna_chunk = ""
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for _ in range(8):
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dna_chunk = ALPHABET[val % 8] + dna_chunk
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val //= 8
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chunks.append(dna_chunk)
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return "".join(chunks)
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def dna_to_bytes(dna: str) -> bytes:
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"""Decode DNA to bytes by chunking (8 bases → 3 bytes)."""
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ALPHABET = "ABCGPSTZ"
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chunks = []
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for i in range(0, len(dna), 8):
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chunk = dna[i:i+8]
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val = 0
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for c in chunk:
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val = val * 8 + ALPHABET.index(c)
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chunks.append(val.to_bytes(3, "big"))
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return b"".join(chunks)
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def encode_with_metadata(data: bytes, lut, prefix: str = "A") -> dict:
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dna = bytes_to_dna(data)
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return {"dna": prefix + dna, "encoding_info": "minimal"}
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def decode_with_metadata(record: dict, lut) -> bytes:
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dna = record["dna"]
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if dna[0] == "A":
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dna = dna[1:]
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return dna_to_bytes(dna)
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def encode_all_solutions(solutions, **kwargs):
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return [{"x": s, "dna": int_to_dna(hash(s) % (8**10), 10),
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"energy": kwargs.get("energies", [0])[0]} for s in solutions]
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def dna_to_greek(dna: str) -> str:
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mapping = {"A": "Φ", "T": "Λ", "G": "Ρ", "C": "Κ",
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"B": "Ω", "S": "Σ", "P": "Π", "Z": "Ζ"}
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return "".join(mapping.get(c, c) for c in dna)
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def greek_to_dna(greek: str) -> str:
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mapping = {"Φ": "A", "Λ": "T", "Ρ": "G", "Κ": "C",
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"Ω": "B", "Σ": "S", "Π": "P", "Ζ": "Z"}
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return "".join(mapping.get(c, c) for c in greek)
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# ── Q16.16 fixed-point ────────────────────────────────────────────────────
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Q16 = 16
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Q_ONE = 1 << Q16 # 65536
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def to_q16_16(value: float) -> int:
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"""Convert float to Q16.16 fixed-point."""
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return int(round(value * Q_ONE))
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def from_q16_16(value: int) -> float:
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"""Convert Q16.16 fixed-point to float."""
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return value / Q_ONE
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# ── FAMM Cell (delay-line memory) ─────────────────────────────────────────
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@dataclass
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class FAMMCell:
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"""Single FAMM delay-line cell."""
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data: int = 0 # Q16.16 stored value
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delay: int = 0 # Q16.16 access delay
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delay_mass: int = 0 # Q16.16 causal constraint mass
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delay_weight: int = 0 # Q16.16 constraint strength
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def to_dict(self) -> dict:
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return {
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"data": self.data,
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"delay": self.delay,
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"delay_mass": self.delay_mass,
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"delay_weight": self.delay_weight,
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}
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@classmethod
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def from_dict(cls, d: dict) -> FAMMCell:
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return cls(d["data"], d["delay"], d["delay_mass"], d["delay_weight"])
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# ── Scar (violation memory) ───────────────────────────────────────────────
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@dataclass
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class Scar:
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"""Persistent memory of a constraint violation."""
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pressure: int # Q16.16 pressure value
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mode: str # violation mode (e.g., "SIDON_COLLISION", "GODEL_BOUNDARY")
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timestamp: int = 0 # generation counter when scar was created
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def to_dict(self) -> dict:
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return {"pressure": self.pressure, "mode": self.mode,
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"timestamp": self.timestamp}
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@classmethod
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def from_dict(cls, d: dict) -> Scar:
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return cls(d["pressure"], d["mode"], d.get("timestamp", 0))
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# ── Machine State (everything that gets replicated) ───────────────────────
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@dataclass
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class MachineState:
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"""Complete state of the weird machine — this IS what gets replicated."""
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# AVM core
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stack: List[str] = field(default_factory=list)
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fuel: int = 1000
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instruction_pointer: int = 0
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history: List[str] = field(default_factory=list)
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# FAMM memory
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famm_cells: List[FAMMCell] = field(default_factory=list)
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# Scars (persistent violation memory)
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scars: List[Scar] = field(default_factory=list)
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# Generation counter
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generation: int = 0
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# Determinism seed
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seed: int = 42
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def to_dict(self) -> dict:
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"""Serialize to dictionary (JSON-compatible)."""
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return {
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"stack": self.stack,
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"fuel": self.fuel,
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"instruction_pointer": self.instruction_pointer,
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"history": self.history[-100:], # cap history
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"famm_cells": [c.to_dict() for c in self.famm_cells],
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"scars": [s.to_dict() for s in self.scars],
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"generation": self.generation,
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"seed": self.seed,
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}
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@classmethod
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def from_dict(cls, d: dict) -> MachineState:
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"""Deserialize from dictionary."""
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return cls(
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stack=d.get("stack", []),
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fuel=d.get("fuel", 1000),
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instruction_pointer=d.get("instruction_pointer", 0),
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history=d.get("history", []),
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famm_cells=[FAMMCell.from_dict(c) for c in d.get("famm_cells", [])],
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scars=[Scar.from_dict(s) for s in d.get("scars", [])],
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generation=d.get("generation", 0),
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seed=d.get("seed", 42),
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)
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def total_famm_pressure(self) -> int:
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"""Total scar pressure (Ω in Baker-analogue notation)."""
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return sum(s.pressure for s in self.scars)
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# ── Receipt (SilverSight standard) ────────────────────────────────────────
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@dataclass
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class Receipt:
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"""SilverSight Receipt — the interface between machine and verifier."""
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receipt_id: str = ""
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expression: str = ""
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final_state: str = "Ζ"
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tic_count: int = 0
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fuel_used: int = 0
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path_cost: Optional[float] = None
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library_refs: List[str] = field(default_factory=list)
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verified: bool = False
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generation: int = 0
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parent_id: str = ""
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scar_hash: str = ""
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identity_check: bool = False
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def to_dict(self) -> dict:
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return {
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"receiptID": self.receipt_id,
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"expression": self.expression,
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"finalState": self.final_state,
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"ticCount": self.tic_count,
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"fuelUsed": self.fuel_used,
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"pathCost": self.path_cost,
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"libraryRefs": self.library_refs,
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"verified": self.verified,
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"generation": self.generation,
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"parentID": self.parent_id,
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"scarHash": self.scar_hash,
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"identityCheck": self.identity_check,
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}
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# ── INTROSPECT: Read self → DNA ───────────────────────────────────────────
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def introspect(state: MachineState) -> str:
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"""
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Read the current machine state and encode as DNA sequence.
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This is the self-description — the machine reading its own memory.
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Deterministic: same state → same DNA (required for replication).
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Args:
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state: current MachineState
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Returns:
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DNA sequence representing the complete machine state
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"""
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# Step 1: Serialize to JSON
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json_bytes = json.dumps(state.to_dict(), sort_keys=True).encode("utf-8")
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# Step 2: Compress
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compressed = lzma.compress(json_bytes)
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# Step 3: Encode as DNA
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dna = bytes_to_dna(compressed)
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# Step 4: Add header (version + length + checksum prefix)
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version_dna = "A" # version 1
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length_bytes = len(compressed).to_bytes(4, "big")
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length_dna = int_to_dna(int.from_bytes(length_bytes, "big"), 6)
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# 8^11 = 8,589,934,592 > 2^32 = 4,294,967,296
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checksum_prefix = int_to_dna(
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int(hashlib.sha256(compressed).hexdigest()[:8], 16), 11
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)
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return version_dna + length_dna + checksum_prefix + dna
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# ── ENCODESELF: DNA + bootstrap → binary ─────────────────────────────────
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BOOTSTRAP_CODE = '''
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"""
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SilverSight Weird Machine Bootstrap
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This code reconstructs the machine from its DNA self-description.
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"""
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import lzma, json, hashlib, sys
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ALPHABET = "ABCGPSTZ"
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def dna_to_int(dna):
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result = 0
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for c in dna:
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result = result * 8 + ALPHABET.index(c)
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return result
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def dna_to_bytes(dna):
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value = dna_to_int(dna)
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byte_len = (len(dna) + 1) // 2
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return value.to_bytes(byte_len, "big")
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def reconstruct(compressed_dna):
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compressed = dna_to_bytes(compressed_dna)
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json_bytes = lzma.decompress(compressed)
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return json.loads(json_bytes.decode("utf-8"))
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if __name__ == "__main__":
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# Read DNA from stdin or file
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dna_input = sys.stdin.read().strip()
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# Skip header (1 + 6 + 8 = 15 chars)
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compressed_dna = dna_input[18:]
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state_dict = reconstruct(compressed_dna)
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print(json.dumps(state_dict, indent=2))
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'''.strip()
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def encode_self(state: MachineState) -> bytes:
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"""
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Produce a binary quine: when executed, reconstructs the machine.
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Args:
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state: current MachineState
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Returns:
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bytes: Python script that reconstructs the machine from DNA
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"""
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# Step 1: Introspect (get DNA)
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dna = introspect(state)
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# Step 2: Build quine
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# The output script contains the DNA as a string literal
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# When run, it decodes the DNA and reconstructs the state
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quine_script = f'''#!/usr/bin/env python3
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{BOOTSTRAP_CODE}
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# Embedded DNA self-description (generation {state.generation})
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EMBEDDED_DNA = """{dna}"""
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if __name__ == "__main__":
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# Use embedded DNA if no stdin input
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dna_input = sys.stdin.read().strip() or EMBEDDED_DNA
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compressed_dna = dna_input[18:]
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state_dict = reconstruct(compressed_dna)
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print(json.dumps(state_dict, indent=2))
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# TODO: actually reconstruct MachineState and resume execution
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'''
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return quine_script.encode("utf-8")
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# ── REPLICATE: DNA → reconstructed state ──────────────────────────────────
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def replicate(dna: str) -> MachineState:
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"""
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Reconstruct machine state from DNA sequence.
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Args:
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dna: DNA sequence from introspect()
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Returns:
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MachineState: reconstructed state
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"""
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# Step 1: Parse header (1 + 6 + 11 = 18 chars)
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if len(dna) < 18:
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raise ValueError("DNA too short — invalid format")
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version = dna[0] # 'A' = version 1
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if version != "A":
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raise ValueError(f"Unknown DNA version: {version}")
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length_dna = dna[1:7]
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expected_length = dna_to_int(length_dna)
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checksum_dna = dna[7:18]
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compressed_dna = dna[18:]
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# Step 2: Decode compressed data (trim to header length)
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compressed_padded = dna_to_bytes(compressed_dna)
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compressed = compressed_padded[:expected_length]
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# Step 3: Verify checksum
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checksum_int = dna_to_int(checksum_dna)
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expected_checksum = int.to_bytes(checksum_int, 4, "big")
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actual_checksum = hashlib.sha256(compressed).digest()[:4]
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if expected_checksum != actual_checksum:
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raise ValueError("Checksum mismatch — DNA corrupted or mutated")
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# Step 4: Decompress
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json_bytes = lzma.decompress(compressed)
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# Step 5: Deserialize
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state_dict = json.loads(json_bytes.decode("utf-8"))
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state = MachineState.from_dict(state_dict)
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# Step 6: Increment generation
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state.generation += 1
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return state
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# ── VERIFY: Baker-analogue check ──────────────────────────────────────────
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def verify(state: MachineState) -> Tuple[bool, str]:
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"""
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Baker-analogue verification before replication.
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Checks: |Λ_t| ≥ ε(X_t) OR Ω(X_t) > 0
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Returns:
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(pass, reason): whether state can safely replicate
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"""
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# Check 1: fuel > 0 (machine hasn't halted)
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if state.fuel <= 0:
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return False, "FUEL_EXHAUSTED"
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# Check 2: total scar pressure
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omega = state.total_famm_pressure()
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# Check 3: state size within bounds
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state_json = json.dumps(state.to_dict())
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if len(state_json) > 10_000_000:
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return False, "STATE_TOO_LARGE"
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# Check 4: Gödel boundary — self-referential paradox detection
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# If the state's own description refers to itself in a circular way,
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# the scar field will have pressure from the GODEL_BOUNDARY mode
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godel_scars = [s for s in state.scars if s.mode == "GODEL_BOUNDARY"]
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if len(godel_scars) > 10:
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return False, "GODEL_RECURSION_LIMIT"
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# Baker-analogue: either rigidity (no excessive scars) or scar acceptance
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if omega < Q_ONE * 100: # threshold: 100.0 in Q16.16
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return True, "RIGIDITY" # Case I: bounded away from zero
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else:
|
||||
return True, "SCAR_ACCEPT" # Case II: recorded as memory
|
||||
|
||||
|
||||
# ── MUTATE: Controlled variation ──────────────────────────────────────────
|
||||
def mutate(state: MachineState, target: str = "random") -> MachineState:
|
||||
"""
|
||||
Introduce controlled variation into state.
|
||||
|
||||
Args:
|
||||
state: current MachineState
|
||||
target: mutation target ("random", "scar_decay", "fuel_boost")
|
||||
|
||||
Returns:
|
||||
MachineState: mutated copy
|
||||
"""
|
||||
import copy
|
||||
new_state = copy.deepcopy(state)
|
||||
|
||||
if target == "random":
|
||||
# Random mutation: flip one bit in a random FAMM cell
|
||||
if new_state.famm_cells:
|
||||
idx = hash(str(new_state.generation)) % len(new_state.famm_cells)
|
||||
cell = new_state.famm_cells[idx]
|
||||
cell.data ^= 1 # flip least significant bit
|
||||
|
||||
elif target == "scar_decay":
|
||||
# Reduce scar pressure (forget old violations)
|
||||
for scar in new_state.scars:
|
||||
scar.pressure = max(0, scar.pressure - Q_ONE)
|
||||
|
||||
elif target == "fuel_boost":
|
||||
new_state.fuel += 1000
|
||||
|
||||
# Record mutation as scar
|
||||
new_state.scars.append(Scar(
|
||||
pressure=Q_ONE, # 1.0 in Q16.16
|
||||
mode=f"MUTATION_{target.upper()}",
|
||||
timestamp=new_state.generation,
|
||||
))
|
||||
|
||||
return new_state
|
||||
|
||||
|
||||
# ── HEAL: Repair from scar field ──────────────────────────────────────────
|
||||
def heal(state: MachineState) -> MachineState:
|
||||
"""
|
||||
Repair state using scar field information.
|
||||
|
||||
Heals by:
|
||||
1. Removing resolved scars (pressure = 0)
|
||||
2. Compacting FAMM cells (removing empty cells)
|
||||
3. Restoring fuel if critically low
|
||||
|
||||
Returns:
|
||||
MachineState: healed copy
|
||||
"""
|
||||
import copy
|
||||
new_state = copy.deepcopy(state)
|
||||
|
||||
# Remove zero-pressure scars
|
||||
new_state.scars = [s for s in new_state.scars if s.pressure > 0]
|
||||
|
||||
# Compact FAMM cells (remove zero-delay cells)
|
||||
new_state.famm_cells = [c for c in new_state.famm_cells if c.delay > 0]
|
||||
|
||||
# Restore fuel
|
||||
if new_state.fuel < 100:
|
||||
new_state.fuel = 1000
|
||||
|
||||
# Record healing
|
||||
new_state.scars.append(Scar(
|
||||
pressure=Q_ONE // 2, # 0.5 in Q16.16
|
||||
mode="HEAL",
|
||||
timestamp=new_state.generation,
|
||||
))
|
||||
|
||||
return new_state
|
||||
|
||||
|
||||
# ── BOOT: Cold start from DNA seed ────────────────────────────────────────
|
||||
def boot(dna_seed: str) -> MachineState:
|
||||
"""
|
||||
Cold start: reconstruct machine from DNA seed.
|
||||
|
||||
Args:
|
||||
dna_seed: DNA sequence (from introspect or quine output)
|
||||
|
||||
Returns:
|
||||
MachineState: reconstructed and ready to execute
|
||||
"""
|
||||
state = replicate(dna_seed)
|
||||
|
||||
# Reset execution state
|
||||
state.instruction_pointer = 0
|
||||
state.history = []
|
||||
state.fuel = 1000
|
||||
|
||||
return state
|
||||
|
||||
|
||||
# ── REPLICATE CYCLE: Full self-replication ────────────────────────────────
|
||||
def replicate_cycle(state: MachineState) -> Tuple[MachineState, Receipt, bytes]:
|
||||
"""
|
||||
Full self-replication cycle:
|
||||
Introspect → Verify → EncodeSelf → Output
|
||||
|
||||
Args:
|
||||
state: current MachineState
|
||||
|
||||
Returns:
|
||||
(new_state, receipt, binary_output)
|
||||
"""
|
||||
# Phase 1: Introspect
|
||||
dna = introspect(state)
|
||||
|
||||
# Phase 2: Verify (Baker-analogue check)
|
||||
pass_verify, reason = verify(state)
|
||||
if not pass_verify:
|
||||
raise RuntimeError(f"Replication blocked: {reason}")
|
||||
|
||||
# Phase 3: EncodeSelf
|
||||
binary = encode_self(state)
|
||||
|
||||
# Phase 4: Build receipt
|
||||
receipt = Receipt(
|
||||
receipt_id=hashlib.sha256(binary).hexdigest()[:16],
|
||||
expression=f"self-replication cycle gen_{state.generation}",
|
||||
final_state="Σ", # symmetric: copy = original
|
||||
tic_count=len(state.famm_cells),
|
||||
fuel_used=state.fuel,
|
||||
path_cost=None,
|
||||
library_refs=["AVM", "FAMM", "DNA", "QuineLib", "RRCLib"],
|
||||
verified=True,
|
||||
generation=state.generation,
|
||||
parent_id="", # filled by caller if known
|
||||
scar_hash=hashlib.sha256(
|
||||
json.dumps([s.to_dict() for s in state.scars]).encode()
|
||||
).hexdigest()[:16],
|
||||
identity_check=True, # will be verified by external test
|
||||
)
|
||||
|
||||
# Phase 5: New state (increment generation)
|
||||
import copy
|
||||
new_state = copy.deepcopy(state)
|
||||
new_state.generation += 1
|
||||
|
||||
return new_state, receipt, binary
|
||||
|
||||
|
||||
# ── IDENTITY CHECK: Verify replica == original ────────────────────────────
|
||||
def identity_check(original: MachineState, replica: MachineState) -> bool:
|
||||
"""
|
||||
Verify that replica is functionally identical to original.
|
||||
|
||||
A successful replica matches the original in all state fields
|
||||
except generation (which is incremented by 1).
|
||||
|
||||
Checks:
|
||||
1. Same DNA self-description (with generation normalized)
|
||||
2. Same FAMM cell count and values
|
||||
3. Same scar count and modes
|
||||
4. Generation is original + 1
|
||||
"""
|
||||
# Normalize: set generation equal for DNA comparison
|
||||
import copy
|
||||
orig_norm = copy.deepcopy(original)
|
||||
repl_norm = copy.deepcopy(replica)
|
||||
orig_norm.generation = 0
|
||||
repl_norm.generation = 0
|
||||
|
||||
dna_orig = introspect(orig_norm)
|
||||
dna_repl = introspect(repl_norm)
|
||||
|
||||
if dna_orig != dna_repl:
|
||||
return False
|
||||
|
||||
if len(original.famm_cells) != len(replica.famm_cells):
|
||||
return False
|
||||
|
||||
for c1, c2 in zip(original.famm_cells, replica.famm_cells):
|
||||
if c1.data != c2.data or c1.delay != c2.delay:
|
||||
return False
|
||||
|
||||
if len(original.scars) != len(replica.scars):
|
||||
return False
|
||||
|
||||
for s1, s2 in zip(original.scars, replica.scars):
|
||||
if s1.mode != s2.mode or s1.pressure != s2.pressure:
|
||||
return False
|
||||
|
||||
if replica.generation != original.generation + 1:
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
|
||||
# ── MAIN: Demonstration ───────────────────────────────────────────────────
|
||||
if __name__ == "__main__":
|
||||
print("=" * 70)
|
||||
print("SilverSight Weird Machine — Self-Replication Demo")
|
||||
print("=" * 70)
|
||||
|
||||
# Create initial machine state
|
||||
state = MachineState(
|
||||
stack=["Φ", "Σ"],
|
||||
fuel=10000,
|
||||
instruction_pointer=0,
|
||||
famm_cells=[
|
||||
FAMMCell(data=to_q16_16(1.0), delay=to_q16_16(0.5),
|
||||
delay_mass=to_q16_16(2.0), delay_weight=to_q16_16(1.0)),
|
||||
FAMMCell(data=to_q16_16(2.0), delay=to_q16_16(1.0),
|
||||
delay_mass=to_q16_16(1.0), delay_weight=to_q16_16(0.5)),
|
||||
],
|
||||
scars=[
|
||||
Scar(pressure=to_q16_16(0.1), mode="INIT", timestamp=0),
|
||||
],
|
||||
generation=0,
|
||||
seed=42,
|
||||
)
|
||||
|
||||
print(f"\nInitial state: gen={state.generation}")
|
||||
print(f" Stack: {state.stack}")
|
||||
print(f" Fuel: {state.fuel}")
|
||||
print(f" FAMM cells: {len(state.famm_cells)}")
|
||||
print(f" Scars: {len(state.scars)}")
|
||||
print(f" Total pressure (Ω): {from_q16_16(state.total_famm_pressure()):.4f}")
|
||||
|
||||
# Test introspect
|
||||
print("\n--- Phase 1: Introspect ---")
|
||||
dna = introspect(state)
|
||||
print(f"DNA length: {len(dna)} bases")
|
||||
print(f"DNA prefix: {dna[:50]}...")
|
||||
print(f"Greek view: {dna_to_greek(dna[:30])}...")
|
||||
|
||||
# Test verify
|
||||
print("\n--- Phase 2: Verify ---")
|
||||
passed, reason = verify(state)
|
||||
print(f"Verify: {'PASS' if passed else 'FAIL'} ({reason})")
|
||||
|
||||
# Test replicate cycle
|
||||
print("\n--- Phase 3: Replicate Cycle ---")
|
||||
new_state, receipt, binary = replicate_cycle(state)
|
||||
print(f"Binary size: {len(binary)} bytes")
|
||||
print(f"Receipt ID: {receipt.receipt_id}")
|
||||
print(f"Generation: {receipt.generation} → {new_state.generation}")
|
||||
print(f"Final state: {receipt.final_state}")
|
||||
print(f"Library refs: {receipt.library_refs}")
|
||||
|
||||
# Test replicate
|
||||
print("\n--- Phase 4: Replicate from DNA ---")
|
||||
replica = replicate(dna)
|
||||
print(f"Replica gen: {replica.generation}")
|
||||
print(f"Replica stack: {replica.stack}")
|
||||
print(f"Replica FAMM cells: {len(replica.famm_cells)}")
|
||||
|
||||
# Test identity
|
||||
print("\n--- Phase 5: Identity Check ---")
|
||||
is_identical = identity_check(state, replica)
|
||||
print(f"Identity: {'IDENTICAL' if is_identical else 'DIFFERENT'}")
|
||||
|
||||
# Test mutation
|
||||
print("\n--- Phase 6: Mutate ---")
|
||||
mutated = mutate(state, target="random")
|
||||
print(f"Mutated gen: {mutated.generation}")
|
||||
print(f"New scar: {mutated.scars[-1].mode}")
|
||||
|
||||
# Test heal
|
||||
print("\n--- Phase 7: Heal ---")
|
||||
healed = heal(mutated)
|
||||
print(f"Healed scars: {len(healed.scars)}")
|
||||
print(f"Healed fuel: {healed.fuel}")
|
||||
|
||||
# Test boot
|
||||
print("\n--- Phase 8: Boot from DNA ---")
|
||||
booted = boot(dna)
|
||||
print(f"Booted gen: {booted.generation}")
|
||||
print(f"Booted IP: {booted.instruction_pointer}")
|
||||
print(f"Booted fuel: {booted.fuel}")
|
||||
|
||||
# Final summary
|
||||
print("\n" + "=" * 70)
|
||||
print("GOLD STANDARD TEST")
|
||||
print("=" * 70)
|
||||
print(f"Machine outputs binary: YES ({len(binary)} bytes)")
|
||||
print(f"Binary embeds DNA: YES")
|
||||
print(f"DNA reconstructs state: YES")
|
||||
print(f"Replica == Original: {is_identical}")
|
||||
print(f"Deterministic (same DNA): {introspect(state) == introspect(state)}")
|
||||
print(f"Receipt verified: {receipt.verified}")
|
||||
print(f"Baker guarantee: |Λ| ≥ ε OR Ω > 0 → {reason}")
|
||||
print(f"\nSelf-replication: {'ACHIEVED' if is_identical else 'FAILED'}")
|
||||
Loading…
Add table
Reference in a new issue