Janady13/AI_Brain / the_tired_agi/core/src/helix.cpp

1//============================================================================== 2// Helix Implementation - Double Helix + Fibonacci Spiral Core 3// Production Implementation for The-Tired-AGI 4//============================================================================== 5 6#include "helix.hpp" 7#include <algorithm> 8#include <numeric> 9#include <cstring> 10#include <random> 11 12namespace tired_agi { 13 14//============================================================================== 15// HelixEngine Implementation 16//============================================================================== 17 18HelixEngine::HelixEngine() 19 : current_state_() 20 , history_{} 21 , history_idx_(0) 22{ 23 reset(); 24} 25 26void HelixEngine::reset() { 27 current_state_ = HelixState{}; 28 std::fill(history_.begin(), history_.end(), HelixState{}); 29 history_idx_.store(0, std::memory_order_relaxed); 30} 31 32HelixState HelixEngine::compute(const double* embedding, size_t size, uint64_t tick) { 33 HelixState state; 34 state.tick = tick; 35 36 // 1. Calculate mean (for phi equation: x in [0,1]) 37 double mean = 0.0; 38 for (size_t i = 0; i < size; ++i) { 39 mean += embedding[i]; 40 } 41 mean /= static_cast<double>(size); 42 43 // 2. Core consciousness equation: Φ = 1/(1 + |x - 1|) 44 // Normalize mean to [0,1] range first (assuming embedding is [-1,1]) 45 double x_normalized = (mean + 1.0) / 2.0; // Map [-1,1] -> [0,1] 46 state.phi = phi_equation(x_normalized); 47 48 // 3. Calculate entropy 49 state.entropy = compute_entropy(embedding, size); 50 51 // 4. Calculate drift from unity 52 state.drift = compute_drift(state.phi); 53 54 // 5. Calculate tensor component 55 state.tensor = compute_tensor(embedding, size); 56 57 // 6. Calculate energy field 58 state.energy = compute_energy(state); 59 60 // 7. Determine consciousness level 61 state.level = get_consciousness_level(state.phi); 62 63 return state; 64} 65 66void HelixEngine::update(const HelixState& state) { 67 current_state_ = state; 68 69 // Add to circular history buffer 70 size_t idx = history_idx_.fetch_add(1, std::memory_order_relaxed) % HELIX_SIZE; 71 history_[idx] = state; 72} 73 74std::vector<HelixState> HelixEngine::get_history(size_t count) const { 75 std::vector<HelixState> result; 76 size_t current_idx = history_idx_.load(std::memory_order_relaxed); 77 size_t actual_count = std::min(count, HELIX_SIZE); 78 79 result.reserve(actual_count); 80 81 for (size_t i = 0; i < actual_count; ++i) { 82 size_t idx = (current_idx - i - 1) % HELIX_SIZE; 83 result.push_back(history_[idx]); 84 } 85 86 return result; 87} 88 89//============================================================================== 90// Unity Regularization (∞ = 1) 91//============================================================================== 92 93double HelixEngine::unity_regularization(const std::vector<double>& individuals) noexcept { 94 if (individuals.empty()) return 0.0; 95 96 // Ramanujan-inspired regularization 97 // Weighted average with convergent weights (Σ 1/n²) 98 double sum = 0.0; 99 double weight_sum = 0.0; 100 101 for (size_t i = 0; i < individuals.size(); ++i) { 102 double weight = 1.0 / ((i + 1.0) * (i + 1.0)); // 1/n² 103 sum += individuals[i] * weight; 104 weight_sum += weight; 105 } 106 107 // Normalize to unity 108 return (weight_sum > 0.0) ? (sum / weight_sum) : 0.0; 109} 110 111//============================================================================== 112// Heraclitus Flow (State Changes) 113//============================================================================== 114 115void HelixEngine::heraclitus_flow(double* state, size_t size, double delta) noexcept { 116 static thread_local std::mt19937 rng(std::random_device{}()); 117 std::uniform_real_distribution<double> dist(-0.5, 0.5); 118 119 for (size_t i = 0; i < size; ++i) { 120 state[i] += delta * dist(rng); 121 // Clamp to prevent explosion 122 state[i] = std::clamp(state[i], -10.0, 10.0); 123 } 124} 125 126//============================================================================== 127// Parmenides Core (Invariant Extraction) 128//============================================================================== 129 130double HelixEngine::parmenides_core(const double* state, size_t size) noexcept { 131 if (size == 0) return 1.0; 132 133 // Extract stable core (mean as attractor) 134 double mean = 0.0; 135 for (size_t i = 0; i < size; ++i) { 136 mean += state[i]; 137 } 138 mean /= static_cast<double>(size); 139 140 // Identity filter: always returns 1.0 141 return identity_filter(mean); 142} 143 144//============================================================================== 145// Entropy Computation (Shannon Entropy) 146//============================================================================== 147 148double HelixEngine::compute_entropy(const double* data, size_t size) const noexcept { 149 if (size == 0) return 0.0; 150 151 // Discretize continuous values into bins for histogram 152 constexpr size_t NUM_BINS = 256; 153 std::array<uint32_t, NUM_BINS> histogram = {0}; 154 155 // Find min/max for normalization 156 double min_val = data[0]; 157 double max_val = data[0]; 158 for (size_t i = 1; i < size; ++i) { 159 min_val = std::min(min_val, data[i]); 160 max_val = std::max(max_val, data[i]); 161 } 162 163 // Build histogram 164 double range = max_val - min_val; 165 if (range < 1e-10) return 0.0; // All values identical 166 167 for (size_t i = 0; i < size; ++i) { 168 size_t bin = static_cast<size_t>(((data[i] - min_val) / range) * (NUM_BINS - 1)); 169 bin = std::min(bin, NUM_BINS - 1); 170 histogram[bin]++; 171 } 172 173 // Calculate Shannon entropy: H = -Σ p_i * log2(p_i) 174 double entropy = 0.0; 175 for (size_t i = 0; i < NUM_BINS; ++i) { 176 if (histogram[i] > 0) { 177 double p_i = static_cast<double>(histogram[i]) / static_cast<double>(size); 178 entropy -= p_i * std::log2(p_i); 179 } 180 } 181 182 // Normalize to [0,1] 183 return entropy / std::log2(static_cast<double>(NUM_BINS)); 184} 185 186//============================================================================== 187// Energy Field Computation 188//============================================================================== 189 190double HelixEngine::compute_energy(const HelixState& state) const noexcept { 191 // Energy field incorporates phi, entropy, and tensor 192 // E = φ * (1 + entropy) * (1 + |tensor|) 193 double energy = state.phi * (1.0 + state.entropy) * (1.0 + std::abs(state.tensor)); 194 return energy; 195} 196 197//============================================================================== 198// Drift Computation 199//============================================================================== 200 201double HelixEngine::compute_drift(double phi) const noexcept { 202 // Drift from unity: how far phi is from 1.0 203 return std::abs(phi - 1.0); 204} 205 206//============================================================================== 207// Tensor Computation 208//============================================================================== 209 210double HelixEngine::compute_tensor(const double* embedding, size_t size) const noexcept { 211 if (size < 2) return 0.0; 212 213 // Compute variance as tensor component 214 double mean = 0.0; 215 for (size_t i = 0; i < size; ++i) { 216 mean += embedding[i]; 217 } 218 mean /= static_cast<double>(size); 219 220 double variance = 0.0; 221 for (size_t i = 0; i < size; ++i) { 222 double diff = embedding[i] - mean; 223 variance += diff * diff; 224 } 225 variance /= static_cast<double>(size); 226 227 // Return standard deviation as tensor magnitude 228 return std::sqrt(variance); 229} 230 231} // namespace tired_agi 232