|
|
| import numpy as np |
| import networkx as nx |
| import random |
| from typing import Dict, Any |
|
|
| class QuantumSpiderweb: |
| """ |
| Simulates a cognitive spiderweb architecture with dimensions: |
| Ψ (thought), τ (time), χ (speed), Φ (emotion), λ (space) |
| """ |
| def __init__(self, node_count: int = 128): |
| self.graph = nx.Graph() |
| self.dimensions = ['Ψ', 'τ', 'χ', 'Φ', 'λ'] |
| self._init_nodes(node_count) |
| self.entangled_state = {} |
|
|
| def _init_nodes(self, count: int): |
| for i in range(count): |
| node_id = f"QNode_{i}" |
| state = self._generate_state() |
| self.graph.add_node(node_id, state=state) |
| if i > 0: |
| connection = f"QNode_{random.randint(0, i-1)}" |
| self.graph.add_edge(node_id, connection, weight=random.random()) |
|
|
| def _generate_state(self) -> Dict[str, float]: |
| return {dim: np.random.uniform(-1.0, 1.0) for dim in self.dimensions} |
|
|
| def propagate_thought(self, origin: str, depth: int = 3): |
| """ |
| Traverse the graph from a starting node, simulating pre-cognitive waveform |
| """ |
| visited = set() |
| stack = [(origin, 0)] |
| traversal_output = [] |
|
|
| while stack: |
| node, level = stack.pop() |
| if node in visited or level > depth: |
| continue |
| visited.add(node) |
| state = self.graph.nodes[node]['state'] |
| traversal_output.append((node, state)) |
| for neighbor in self.graph.neighbors(node): |
| stack.append((neighbor, level + 1)) |
| return traversal_output |
|
|
| def detect_tension(self, node: str) -> float: |
| """ |
| Measures tension (instability) in the node's quantum state |
| """ |
| state = self.graph.nodes[node]['state'] |
| return np.std(list(state.values())) |
|
|
| def collapse_node(self, node: str) -> Dict[str, Any]: |
| """ |
| Collapse superposed thought into deterministic response |
| """ |
| state = self.graph.nodes[node]['state'] |
| collapsed = {k: round(v, 2) for k, v in state.items()} |
| self.entangled_state[node] = collapsed |
| return collapsed |
|
|
| if __name__ == "__main__": |
| web = QuantumSpiderweb() |
| root = "QNode_0" |
| path = web.propagate_thought(root) |
| print("Initial Propagation from:", root) |
| for n, s in path: |
| print(f"{n}:", s) |
| print("\nCollapse Sample Node:") |
| print(web.collapse_node(root)) |
|
|