collaborative-swarm-coordinator

• Emergent Intelligence - Simple agent rules create complex collective behaviors • Distributed Consensus - No single point of failure or central authority • Byzantine Fault Tolerance - Handle malicious or faulty agents gracefully • Eventually Consistent - Converge to agreement despite network partitions • Self-Organizing - Adaptive topology based on task requirements

Hierarchical Swarm Architecture: `python from typing import Dict, List, Set, Optional import asyncio from dataclasses import dataclass from enum import Enum class AgentRole(Enum): COORDINATOR = "coordinator" WORKER = "worker" VALIDATOR = "validator" OBSERVER = "observer" @dataclass class SwarmAgent: id: str role: AgentRole capabilities: Set[str] reputation: float = 1.0 active_tasks: List[str] = None def __post_init__(self): self.active_tasks = self.active_tasks or [] class CollaborativeSwarm: def __init__(self, min_agents: int = 3, max_agents: int = 100): self.agents: Dict[str, SwarmAgent] = {} self.task_queue = asyncio.Queue() self.consensus_threshold = 0.67 # 2/3 majority self.min_agents = min_agents self.max_agents = max_agents self.topology = "mesh" # mesh, star, ring, hierarchical async def spawn_agent(self, capabilities: Set[str]) -> SwarmAgent: """Dynamically spawn new agent based on workload""" if len(self.agents) >= self.max_agents: return None agent = SwarmAgent( id=self.generate_agent_id(), role=self.determine_role(capabilities), capabilities=capabilities ) # Byzantine agreement on new agent if await self.byzantine_consensus(f"spawn_{agent.id}"): self.agents[agent.id] = agent await self.gossip_agent_joined(agent) return agent return None async def byzantine_consensus(self, proposal: str) -> bool: """Practical Byzantine Fault Tolerance (PBFT) consensus""" votes = {} round_number = 0 max_rounds = 3 while round_number < max_rounds: # Prepare phase prepare_votes = await self.broadcast_prepare(proposal, round_number) if len(prepare_votes) > len(self.agents) * self.consensus_threshold: # Commit phase commit_votes = await self.broadcast_commit(proposal, round_number) if len(commit_votes) > len(self.agents) * self.consensus_threshold: return True round_number += 1 await asyncio.sleep(0.1 (2 * round_number)) # Exponential backoff return False async def gossip_protocol(self, message: Dict): """Epidemic-style information dissemination""" infected = set() susceptible = set(self.agents.keys()) # Patient zero if susceptible: initial = susceptible.pop() infected.add(initial) await self.agents[initial].receive_gossip(message) rounds = 0 while susceptible and rounds < self.log_n_rounds(): new_infected = set() for agent_id in infected: # Each infected agent spreads to k random agents targets = self.select_gossip_targets( agent_id, susceptible, k=3 # Fanout factor ) for target in targets: if target in susceptible: await self.agents[target].receive_gossip(message) new_infected.add(target) susceptible.remove(target) infected.update(new_infected) rounds += 1 def log_n_rounds(self) -> int: """Calculate O(log n) rounds for gossip convergence""" import math return max(1, int(math.log2(len(self.agents) + 1)) + 2) async def coordinate_task(self, task: Dict): """Coordinate task execution across swarm""" # Task decomposition subtasks = self.decompose_task(task) # Agent selection using reputation assignments = {} for subtask in subtasks: eligible = self.find_capable_agents(subtask['required_capabilities']) if eligible: # Weighted random selection by reputation agent = self.select_by_reputation(eligible) assignments[subtask['id']] = agent.id agent.active_tasks.append(subtask['id']) # Parallel execution with monitoring results = await self.execute_parallel(assignments, subtasks) # Validation through consensus if await self.validate_results(results): await self.update_reputations(assignments, results) return self.merge_results(results) # Retry with different agents if validation fails return await self.retry_with_reassignment(task, assignments) ` Mesh Topology Coordination: `typescript // TypeScript - Peer-to-peer mesh coordination interface MeshNode { id: string; peers: Set<string>; state: Map<string, any>; vector_clock: Map<string, number>; } class MeshCoordinator { private nodes: Map<string, MeshNode> = new Map(); private connections: Map<string, Set<string>> = new Map(); async formMesh(nodeCount: number): Promise<void> { // Create fully connected mesh initially for (let i = 0; i < nodeCount; i++) { const node: MeshNode = { id: node_${i}, peers: new Set(), state: new Map(), vector_clock: new Map([[node_${i}, 0]]) }; // Connect to all other nodes for (let j = 0; j < nodeCount; j++) { if (i !== j) { node.peers.add(node_${j}); } } this.nodes.set(node.id, node); } // Optimize topology based on communication patterns await this.optimizeTopology(); } async optimizeTopology(): Promise<void> { // Use spring-force algorithm to optimize connections const iterations = 100; const idealConnections = Math.log2(this.nodes.size) * 2; for (let i = 0; i < iterations; i++) { for (const [nodeId, node] of this.nodes) { // Remove underutilized connections const utilization = await this.measureLinkUtilization(nodeId); const toRemove = Array.from(node.peers) .filter(peer => utilization.get(peer) < 0.1) .slice(0, node.peers.size - idealConnections); toRemove.forEach(peer => { node.peers.delete(peer); this.nodes.get(peer)?.peers.delete(nodeId); }); // Add connections to frequently accessed nodes const candidates = await this.findConnectionCandidates(nodeId); const toAdd = candidates.slice(0, idealConnections - node.peers.size); toAdd.forEach(peer => { node.peers.add(peer); this.nodes.get(peer)?.peers.add(nodeId); }); } } } async broadcast(sourceId: string, message: any): Promise<void> { // Efficient broadcast using spanning tree const visited = new Set<string>([sourceId]); const queue: Array<{nodeId: string, ttl: number}> = [ {nodeId: sourceId, ttl: this.calculateTTL()} ]; while (queue.length > 0) { const {nodeId, ttl} = queue.shift()!; if (ttl <= 0) continue; const node = this.nodes.get(nodeId); if (!node) continue; // Forward to unvisited peers for (const peer of node.peers) { if (!visited.has(peer)) { visited.add(peer); await this.deliverMessage(peer, message); queue.push({nodeId: peer, ttl: ttl - 1}); } } } } private calculateTTL(): number { // Diameter of the network return Math.ceil(Math.log2(this.nodes.size)) + 2; } } `

Raft Consensus Implementation: `rust // Rust - Raft consensus for leader election and log replication use std::sync::{Arc, Mutex}; use std::collections::{HashMap, VecDeque}; use tokio::time::{interval, Duration}; #[derive(Debug, Clone, PartialEq)] enum NodeState { Follower, Candidate, Leader, } #[derive(Debug, Clone)] struct LogEntry { term: u64, index: u64, command: String, } struct RaftNode { id: String, state: Arc<Mutex<NodeState>>, current_term: Arc<Mutex<u64>>, voted_for: Arc<Mutex<Option<String>>>, log: Arc<Mutex<Vec<LogEntry>>>, peers: Vec<String>, leader_id: Arc<Mutex<Option<String>>>, } impl RaftNode { async fn run(&self) { let mut election_timer = interval(Duration::from_millis( rand::random::<u64>() % 150 + 150 // 150-300ms )); loop { election_timer.tick().await; let state = self.state.lock().unwrap().clone(); match state { NodeState::Follower => { // Start election if no heartbeat received self.become_candidate().await; } NodeState::Candidate => { // Request votes from peers let won = self.request_votes().await;