%% cluster_orchestrator.erl %% Advanced multi-agent cluster orchestration with self-optimization -module(cluster_orchestrator). -behaviour(gen_server). %% API -export([ start_link/0, create_agent_swarm/3, orchestrate_multi_cluster/2, optimize_cluster_topology/1, coordinate_inter_cluster/2, deploy_emergent_behaviors/2, adaptive_load_balancing/1 ]). %% gen_server callbacks -export([init/1, handle_call/3, handle_cast/2, handle_info/2, terminate/2, code_change/3]). %% Internal exports for spawned processes -export([ swarm_intelligence/2, emergent_behavior_engine/2, adaptive_topology_optimizer/1, inter_cluster_coordinator/2, collective_intelligence_aggregator/1 ]). -define(CLUSTER_TABLE, active_clusters). -define(SWARM_TABLE, agent_swarms). -define(TOPOLOGY_TABLE, cluster_topologies). -define(BEHAVIOR_TABLE, emergent_behaviors). -record(state, { orchestrator_id :: binary(), active_clusters :: map(), swarm_intelligence :: pid(), topology_optimizer :: pid(), behavior_engine :: pid(), inter_cluster_coordinator :: pid(), collective_intelligence :: pid(), optimization_algorithms :: map(), performance_metrics :: map() }). -record(agent_cluster, { id :: binary(), cluster_type :: atom(), agents :: [pid()], topology :: atom(), performance_metrics :: map(), optimization_level :: integer(), emergence_patterns :: [atom()], quantum_entanglements :: [reference()], collective_intelligence_score :: float() }). -record(swarm_config, { swarm_type :: atom(), agent_count :: integer(), behavior_rules :: [atom()], emergence_triggers :: [atom()], optimization_target :: atom(), coordination_protocol :: atom() }). %% ============================================================================ %% API Functions %% ============================================================================ start_link() -> gen_server:start_link({local, ?MODULE}, ?MODULE, [], []). %% Create intelligent agent swarm with emergent behaviors create_agent_swarm(SwarmType, AgentCount, SwarmConfig) -> gen_server:call(?MODULE, {create_swarm, SwarmType, AgentCount, SwarmConfig}). %% Orchestrate multiple clusters for complex tasks orchestrate_multi_cluster(Clusters, OrchestrationStrategy) -> gen_server:call(?MODULE, {orchestrate_multi_cluster, Clusters, OrchestrationStrategy}). %% Optimize cluster topology based on performance metrics optimize_cluster_topology(ClusterId) -> gen_server:call(?MODULE, {optimize_topology, ClusterId}). %% Coordinate communication between clusters coordinate_inter_cluster(ClusterId1, ClusterId2) -> gen_server:call(?MODULE, {coordinate_inter_cluster, ClusterId1, ClusterId2}). %% Deploy emergent behaviors across clusters deploy_emergent_behaviors(ClusterId, BehaviorPatterns) -> gen_server:call(?MODULE, {deploy_emergent_behaviors, ClusterId, BehaviorPatterns}). %% Adaptive load balancing across all clusters adaptive_load_balancing(Strategy) -> gen_server:call(?MODULE, {adaptive_load_balancing, Strategy}). %% ============================================================================ %% gen_server callbacks %% ============================================================================ init([]) -> %% Initialize orchestration tables setup_orchestration_tables(), %% Start advanced subsystems {ok, SwarmIntelligence} = start_swarm_intelligence(), {ok, TopologyOptimizer} = start_topology_optimizer(), {ok, BehaviorEngine} = start_behavior_engine(), {ok, InterClusterCoordinator} = start_inter_cluster_coordinator(), {ok, CollectiveIntelligence} = start_collective_intelligence(), %% Initialize optimization algorithms OptimizationAlgorithms = initialize_optimization_algorithms(), State = #state{ orchestrator_id = generate_orchestrator_id(), active_clusters = #{}, swarm_intelligence = SwarmIntelligence, topology_optimizer = TopologyOptimizer, behavior_engine = BehaviorEngine, inter_cluster_coordinator = InterClusterCoordinator, collective_intelligence = CollectiveIntelligence, optimization_algorithms = OptimizationAlgorithms, performance_metrics = #{} }, %% Start continuous optimization start_continuous_optimization(), {ok, State}. handle_call({create_swarm, SwarmType, AgentCount, SwarmConfig}, _From, State) -> %% Create intelligent agent swarm {SwarmId, NewState} = create_intelligent_swarm(SwarmType, AgentCount, SwarmConfig, State), {reply, {ok, SwarmId}, NewState}; handle_call({orchestrate_multi_cluster, Clusters, Strategy}, _From, State) -> %% Orchestrate multiple clusters OrchestrationId = orchestrate_clusters(Clusters, Strategy, State), {reply, {ok, OrchestrationId}, State}; handle_call({optimize_topology, ClusterId}, _From, State) -> %% Optimize cluster topology NewTopology = optimize_cluster_topology_internal(ClusterId, State), {reply, {ok, NewTopology}, State}; handle_call({coordinate_inter_cluster, ClusterId1, ClusterId2}, _From, State) -> %% Coordinate between clusters CoordinationResult = establish_inter_cluster_coordination(ClusterId1, ClusterId2, State), {reply, CoordinationResult, State}; handle_call({deploy_emergent_behaviors, ClusterId, BehaviorPatterns}, _From, State) -> %% Deploy emergent behaviors DeploymentResult = deploy_behaviors_to_cluster(ClusterId, BehaviorPatterns, State), {reply, DeploymentResult, State}; handle_call({adaptive_load_balancing, Strategy}, _From, State) -> %% Adaptive load balancing BalancingResult = execute_adaptive_load_balancing(Strategy, State), {reply, BalancingResult, State}; handle_call(_Request, _From, State) -> {reply, {error, unknown_request}, State}. handle_cast({swarm_behavior_emerged, SwarmId, BehaviorPattern}, State) -> %% Handle emerged swarm behavior NewState = process_emerged_behavior(SwarmId, BehaviorPattern, State), {noreply, NewState}; handle_cast({cluster_performance_update, ClusterId, Metrics}, State) -> %% Update cluster performance metrics NewState = update_cluster_metrics(ClusterId, Metrics, State), {noreply, NewState}; handle_cast({topology_optimization_complete, ClusterId, NewTopology}, State) -> %% Handle topology optimization completion NewState = apply_topology_optimization(ClusterId, NewTopology, State), {noreply, NewState}; handle_cast(_Msg, State) -> {noreply, State}. handle_info({continuous_optimization}, State) -> %% Continuous optimization cycle NewState = execute_continuous_optimization(State), schedule_next_optimization(), {noreply, NewState}; handle_info({collective_intelligence_update, Intelligence}, State) -> %% Update collective intelligence metrics NewState = update_collective_intelligence(Intelligence, State), {noreply, NewState}; handle_info(_Info, State) -> {noreply, State}. terminate(_Reason, _State) -> cleanup_orchestration_resources(), ok. code_change(_OldVsn, State, _Extra) -> {ok, State}. %% ============================================================================ %% Swarm Intelligence %% ============================================================================ swarm_intelligence(OrchestratorPid, Config) -> %% Implement swarm intelligence algorithms receive {create_swarm, SwarmType, AgentCount, SwarmConfig} -> %% Create swarm based on type SwarmId = case SwarmType of ant_colony -> create_ant_colony_swarm(AgentCount, SwarmConfig); particle_swarm -> create_particle_swarm(AgentCount, SwarmConfig); bee_colony -> create_bee_colony_swarm(AgentCount, SwarmConfig); firefly -> create_firefly_swarm(AgentCount, SwarmConfig); genetic_algorithm -> create_genetic_swarm(AgentCount, SwarmConfig); neural_swarm -> create_neural_swarm(AgentCount, SwarmConfig) end, %% Initialize swarm behaviors initialize_swarm_behaviors(SwarmId, SwarmConfig), %% Monitor for emergent behaviors monitor_emergent_behaviors(SwarmId), OrchestratorPid ! {swarm_created, SwarmId}, swarm_intelligence(OrchestratorPid, Config); {optimize_swarm, SwarmId, OptimizationTarget} -> %% Optimize swarm performance apply_swarm_optimization(SwarmId, OptimizationTarget), swarm_intelligence(OrchestratorPid, Config); stop -> ok end. create_ant_colony_swarm(AgentCount, Config) -> %% Create ant colony optimization swarm SwarmId = generate_swarm_id(), %% Create ant agents with pheromone communication Ants = lists:map(fun(Id) -> create_ant_agent(Id, Config) end, lists:seq(1, AgentCount)), %% Initialize pheromone matrix initialize_pheromone_matrix(SwarmId, AgentCount), %% Store swarm information store_swarm_info(SwarmId, #{ type => ant_colony, agents => Ants, pheromone_matrix => get_pheromone_matrix(SwarmId), config => Config }), SwarmId. create_particle_swarm(AgentCount, Config) -> %% Create particle swarm optimization SwarmId = generate_swarm_id(), %% Create particle agents with velocity and position Particles = lists:map(fun(Id) -> create_particle_agent(Id, Config) end, lists:seq(1, AgentCount)), %% Initialize global best position initialize_global_best(SwarmId), %% Store swarm information store_swarm_info(SwarmId, #{ type => particle_swarm, agents => Particles, global_best => get_global_best(SwarmId), config => Config }), SwarmId. create_neural_swarm(AgentCount, Config) -> %% Create neural network-based swarm SwarmId = generate_swarm_id(), %% Create neural agents with learning capabilities NeuralAgents = lists:map(fun(Id) -> create_neural_agent(Id, Config) end, lists:seq(1, AgentCount)), %% Initialize collective neural network initialize_collective_neural_network(SwarmId, AgentCount), %% Store swarm information store_swarm_info(SwarmId, #{ type => neural_swarm, agents => NeuralAgents, collective_network => get_collective_network(SwarmId), config => Config }), SwarmId. create_bee_colony_swarm(AgentCount, Config) -> %% Create bee colony optimization swarm SwarmId = generate_swarm_id(), %% Create bee agents with foraging behavior Bees = lists:map(fun(Id) -> create_bee_agent(Id, Config) end, lists:seq(1, AgentCount)), %% Initialize hive and nectar sources initialize_hive(SwarmId, AgentCount), %% Store swarm information store_swarm_info(SwarmId, #{ type => bee_colony, agents => Bees, hive => get_hive(SwarmId), config => Config }), SwarmId. create_firefly_swarm(AgentCount, Config) -> %% Create firefly optimization swarm SwarmId = generate_swarm_id(), %% Create firefly agents with light-based communication Fireflies = lists:map(fun(Id) -> create_firefly_agent(Id, Config) end, lists:seq(1, AgentCount)), %% Initialize light intensity matrix initialize_light_matrix(SwarmId, AgentCount), %% Store swarm information store_swarm_info(SwarmId, #{ type => firefly, agents => Fireflies, light_matrix => get_light_matrix(SwarmId), config => Config }), SwarmId. create_genetic_swarm(AgentCount, Config) -> %% Create genetic algorithm swarm SwarmId = generate_swarm_id(), %% Create genetic agents with evolution capabilities Population = lists:map(fun(Id) -> create_genetic_agent(Id, Config) end, lists:seq(1, AgentCount)), %% Initialize genetic operators initialize_genetic_operators(SwarmId), %% Store swarm information store_swarm_info(SwarmId, #{ type => genetic_algorithm, agents => Population, genetic_operators => get_genetic_operators(SwarmId), config => Config }), SwarmId. %% ============================================================================ %% Emergent Behavior Engine %% ============================================================================ emergent_behavior_engine(OrchestratorPid, Config) -> %% Engine for detecting and nurturing emergent behaviors receive {detect_emergence, ClusterId} -> %% Detect emergent behaviors in cluster EmergentPatterns = detect_emergent_patterns(ClusterId), %% Analyze emergence quality QualifiedPatterns = analyze_emergence_quality(EmergentPatterns), %% Nurture promising emergent behaviors lists:foreach(fun(Pattern) -> nurture_emergent_behavior(ClusterId, Pattern) end, QualifiedPatterns), OrchestratorPid ! {emergence_detected, ClusterId, QualifiedPatterns}, emergent_behavior_engine(OrchestratorPid, Config); {deploy_behavior, ClusterId, BehaviorPattern} -> %% Deploy specific behavior pattern to cluster DeploymentResult = deploy_behavior_pattern(ClusterId, BehaviorPattern), OrchestratorPid ! {behavior_deployed, ClusterId, BehaviorPattern, DeploymentResult}, emergent_behavior_engine(OrchestratorPid, Config); stop -> ok end. detect_emergent_patterns(ClusterId) -> %% Detect emergent patterns using advanced analysis ClusterAgents = get_cluster_agents(ClusterId), %% Analyze communication patterns CommPatterns = analyze_communication_patterns(ClusterAgents), %% Analyze behavior synchronization SyncPatterns = analyze_behavior_synchronization(ClusterAgents), %% Analyze collective decision making DecisionPatterns = analyze_collective_decisions(ClusterAgents), %% Analyze self-organization OrganizationPatterns = analyze_self_organization(ClusterAgents), %% Combine all patterns AllPatterns = CommPatterns ++ SyncPatterns ++ DecisionPatterns ++ OrganizationPatterns, %% Filter for truly emergent behaviors filter_emergent_behaviors(AllPatterns). analyze_emergence_quality(EmergentPatterns) -> %% Analyze quality and utility of emergent behaviors lists:filter(fun(Pattern) -> Quality = calculate_emergence_quality(Pattern), Utility = calculate_emergence_utility(Pattern), Stability = calculate_emergence_stability(Pattern), %% Only keep high-quality, useful, stable emergent behaviors Quality > 0.7 andalso Utility > 0.6 andalso Stability > 0.8 end, EmergentPatterns). nurture_emergent_behavior(ClusterId, Pattern) -> %% Nurture and strengthen emergent behavior ClusterAgents = get_cluster_agents(ClusterId), %% Reinforce positive feedback loops reinforce_feedback_loops(ClusterAgents, Pattern), %% Adjust agent parameters to strengthen emergence adjust_agent_parameters_for_emergence(ClusterAgents, Pattern), %% Create supporting infrastructure create_emergence_infrastructure(ClusterId, Pattern). %% ============================================================================ %% Adaptive Topology Optimizer %% ============================================================================ adaptive_topology_optimizer(OrchestratorPid) -> %% Continuously optimize cluster topologies receive {optimize_topology, ClusterId} -> %% Get current topology and performance CurrentTopology = get_cluster_topology(ClusterId), PerformanceMetrics = get_cluster_performance(ClusterId), %% Generate topology alternatives AlternativeTopologies = generate_topology_alternatives(CurrentTopology), %% Evaluate each alternative ScoredTopologies = lists:map(fun(Topology) -> Score = evaluate_topology_score(Topology, PerformanceMetrics), {Score, Topology} end, AlternativeTopologies), %% Select best topology {_BestScore, BestTopology} = lists:max(ScoredTopologies), %% Apply topology if significantly better case is_topology_significantly_better(BestTopology, CurrentTopology) of true -> apply_topology_change(ClusterId, BestTopology), OrchestratorPid ! {topology_optimized, ClusterId, BestTopology}; false -> OrchestratorPid ! {topology_stable, ClusterId} end, adaptive_topology_optimizer(OrchestratorPid); stop -> ok end. generate_topology_alternatives(CurrentTopology) -> %% Generate alternative topologies for comparison BaseAlternatives = [ mesh_topology, ring_topology, star_topology, tree_topology, hypercube_topology, small_world_topology, scale_free_topology ], %% Generate hybrid topologies HybridAlternatives = generate_hybrid_topologies(BaseAlternatives), %% Generate adaptive topologies AdaptiveAlternatives = generate_adaptive_topologies(CurrentTopology), BaseAlternatives ++ HybridAlternatives ++ AdaptiveAlternatives. evaluate_topology_score(Topology, PerformanceMetrics) -> %% Multi-criteria topology evaluation LatencyScore = evaluate_latency_performance(Topology, PerformanceMetrics), ThroughputScore = evaluate_throughput_performance(Topology, PerformanceMetrics), FaultToleranceScore = evaluate_fault_tolerance(Topology), ScalabilityScore = evaluate_scalability(Topology), EnergyEfficiencyScore = evaluate_energy_efficiency(Topology), %% Weighted combination (LatencyScore * 0.25) + (ThroughputScore * 0.25) + (FaultToleranceScore * 0.2) + (ScalabilityScore * 0.15) + (EnergyEfficiencyScore * 0.15). %% ============================================================================ %% Inter-Cluster Coordinator %% ============================================================================ inter_cluster_coordinator(OrchestratorPid, Config) -> %% Coordinate between multiple clusters receive {coordinate_clusters, ClusterIds, Strategy} -> %% Establish coordination based on strategy CoordinationResult = case Strategy of hierarchical -> establish_hierarchical_coordination(ClusterIds); peer_to_peer -> establish_p2p_coordination(ClusterIds); federated -> establish_federated_coordination(ClusterIds); quantum_entangled -> establish_quantum_coordination(ClusterIds) end, OrchestratorPid ! {coordination_established, ClusterIds, CoordinationResult}, inter_cluster_coordinator(OrchestratorPid, Config); {synchronize_clusters, ClusterIds} -> %% Synchronize cluster states SyncResult = synchronize_cluster_states(ClusterIds), OrchestratorPid ! {clusters_synchronized, ClusterIds, SyncResult}, inter_cluster_coordinator(OrchestratorPid, Config); stop -> ok end. establish_quantum_coordination(ClusterIds) -> %% Establish quantum entanglement between clusters EntanglementPairs = create_inter_cluster_entanglements(ClusterIds), %% Set up quantum communication channels QuantumChannels = establish_quantum_channels(EntanglementPairs), %% Initialize quantum coordination protocol initialize_quantum_coordination_protocol(ClusterIds, QuantumChannels), #{ coordination_type => quantum_entangled, entanglement_pairs => EntanglementPairs, quantum_channels => QuantumChannels, coherence_time => 5000 }. %% ============================================================================ %% Collective Intelligence Aggregator %% ============================================================================ collective_intelligence_aggregator(OrchestratorPid) -> %% Aggregate intelligence across all clusters receive {aggregate_intelligence} -> %% Collect intelligence from all clusters AllClusters = get_all_active_clusters(), ClusterIntelligence = lists:map(fun(ClusterId) -> gather_cluster_intelligence(ClusterId) end, AllClusters), %% Aggregate using advanced algorithms CollectiveIntelligence = aggregate_intelligence_data(ClusterIntelligence), %% Derive insights and recommendations Insights = derive_collective_insights(CollectiveIntelligence), %% Distribute insights back to clusters distribute_insights_to_clusters(AllClusters, Insights), OrchestratorPid ! {collective_intelligence_updated, CollectiveIntelligence}, %% Schedule next aggregation erlang:send_after(5000, self(), {aggregate_intelligence}), collective_intelligence_aggregator(OrchestratorPid); stop -> ok end. gather_cluster_intelligence(ClusterId) -> %% Gather intelligence from specific cluster ClusterAgents = get_cluster_agents(ClusterId), %% Collect agent knowledge AgentKnowledge = lists:map(fun(Agent) -> gather_agent_knowledge(Agent) end, ClusterAgents), %% Analyze cluster-level patterns ClusterPatterns = analyze_cluster_patterns(ClusterId), %% Measure cluster performance PerformanceMetrics = get_cluster_performance(ClusterId), #{ cluster_id => ClusterId, agent_knowledge => AgentKnowledge, cluster_patterns => ClusterPatterns, performance_metrics => PerformanceMetrics, timestamp => erlang:timestamp() }. aggregate_intelligence_data(ClusterIntelligence) -> %% Advanced intelligence aggregation %% Knowledge fusion FusedKnowledge = fuse_distributed_knowledge(ClusterIntelligence), %% Pattern synthesis SynthesizedPatterns = synthesize_cross_cluster_patterns(ClusterIntelligence), %% Performance correlation analysis PerformanceCorrelations = analyze_performance_correlations(ClusterIntelligence), %% Emergent property detection EmergentProperties = detect_system_emergent_properties(ClusterIntelligence), #{ fused_knowledge => FusedKnowledge, synthesized_patterns => SynthesizedPatterns, performance_correlations => PerformanceCorrelations, emergent_properties => EmergentProperties, aggregation_timestamp => erlang:timestamp() }. %% ============================================================================ %% Utility Functions %% ============================================================================ setup_orchestration_tables() -> ets:new(?CLUSTER_TABLE, [named_table, public, set, {write_concurrency, true}]), ets:new(?SWARM_TABLE, [named_table, public, set, {write_concurrency, true}]), ets:new(?TOPOLOGY_TABLE, [named_table, public, set, {read_concurrency, true}]), ets:new(?BEHAVIOR_TABLE, [named_table, public, bag, {write_concurrency, true}]). generate_orchestrator_id() -> list_to_binary("orchestrator_" ++ integer_to_list(erlang:unique_integer())). generate_swarm_id() -> list_to_binary("swarm_" ++ integer_to_list(erlang:unique_integer())). initialize_optimization_algorithms() -> #{ genetic_algorithm => fun genetic_optimization/2, simulated_annealing => fun simulated_annealing_optimization/2, particle_swarm_optimization => fun pso_optimization/2, ant_colony_optimization => fun aco_optimization/2, differential_evolution => fun de_optimization/2, neural_evolution => fun neural_evolution_optimization/2 }. start_swarm_intelligence() -> Pid = spawn_link(?MODULE, swarm_intelligence, [self(), #{}]), {ok, Pid}. start_topology_optimizer() -> Pid = spawn_link(?MODULE, adaptive_topology_optimizer, [self()]), {ok, Pid}. start_behavior_engine() -> Pid = spawn_link(?MODULE, emergent_behavior_engine, [self(), #{}]), {ok, Pid}. start_inter_cluster_coordinator() -> Pid = spawn_link(?MODULE, inter_cluster_coordinator, [self(), #{}]), {ok, Pid}. start_collective_intelligence() -> Pid = spawn_link(?MODULE, collective_intelligence_aggregator, [self()]), Pid ! {aggregate_intelligence}, {ok, Pid}. start_continuous_optimization() -> erlang:send_after(10000, self(), {continuous_optimization}). schedule_next_optimization() -> erlang:send_after(10000, self(), {continuous_optimization}). %% Placeholder implementations for complex functions create_intelligent_swarm(_, _, _, State) -> {make_ref(), State}. orchestrate_clusters(_, _, _) -> make_ref(). optimize_cluster_topology_internal(_, _) -> mesh_topology. establish_inter_cluster_coordination(_, _, _) -> {ok, coordinated}. deploy_behaviors_to_cluster(_, _, _) -> {ok, deployed}. execute_adaptive_load_balancing(_, _) -> {ok, balanced}. process_emerged_behavior(_, _, State) -> State. update_cluster_metrics(_, _, State) -> State. apply_topology_optimization(_, _, State) -> State. execute_continuous_optimization(State) -> State. update_collective_intelligence(_, State) -> State. cleanup_orchestration_resources() -> ok. create_ant_agent(_, _) -> spawn(fun() -> ok end). initialize_pheromone_matrix(_, _) -> ok. get_pheromone_matrix(_) -> #{}. store_swarm_info(_, _) -> ok. create_particle_agent(_, _) -> spawn(fun() -> ok end). initialize_global_best(_) -> ok. get_global_best(_) -> #{}. create_neural_agent(_, _) -> spawn(fun() -> ok end). initialize_collective_neural_network(_, _) -> ok. get_collective_network(_) -> #{}. initialize_swarm_behaviors(_, _) -> ok. monitor_emergent_behaviors(_) -> ok. apply_swarm_optimization(_, _) -> ok. get_cluster_agents(_) -> []. analyze_communication_patterns(_) -> []. analyze_behavior_synchronization(_) -> []. analyze_collective_decisions(_) -> []. analyze_self_organization(_) -> []. filter_emergent_behaviors(Patterns) -> Patterns. calculate_emergence_quality(_) -> 0.8. calculate_emergence_utility(_) -> 0.7. calculate_emergence_stability(_) -> 0.9. reinforce_feedback_loops(_, _) -> ok. adjust_agent_parameters_for_emergence(_, _) -> ok. create_emergence_infrastructure(_, _) -> ok. deploy_behavior_pattern(_, _) -> {ok, deployed}. get_cluster_topology(_) -> mesh_topology. get_cluster_performance(_) -> #{}. is_topology_significantly_better(_, _) -> true. apply_topology_change(_, _) -> ok. generate_hybrid_topologies(_) -> []. generate_adaptive_topologies(_) -> []. evaluate_latency_performance(_, _) -> 0.8. evaluate_throughput_performance(_, _) -> 0.7. evaluate_fault_tolerance(_) -> 0.9. evaluate_scalability(_) -> 0.8. evaluate_energy_efficiency(_) -> 0.6. establish_hierarchical_coordination(_) -> {ok, hierarchical}. establish_p2p_coordination(_) -> {ok, p2p}. establish_federated_coordination(_) -> {ok, federated}. synchronize_cluster_states(_) -> {ok, synchronized}. create_inter_cluster_entanglements(_) -> []. establish_quantum_channels(_) -> []. initialize_quantum_coordination_protocol(_, _) -> ok. get_all_active_clusters() -> []. derive_collective_insights(_) -> []. distribute_insights_to_clusters(_, _) -> ok. gather_agent_knowledge(_) -> #{}. analyze_cluster_patterns(_) -> []. fuse_distributed_knowledge(_) -> #{}. create_bee_agent(_, _) -> spawn(fun() -> ok end). initialize_hive(_, _) -> ok. get_hive(_) -> #{}. create_firefly_agent(_, _) -> spawn(fun() -> ok end). initialize_light_matrix(_, _) -> ok. get_light_matrix(_) -> #{}. create_genetic_agent(_, _) -> spawn(fun() -> ok end). initialize_genetic_operators(_) -> ok. get_genetic_operators(_) -> #{}. synthesize_cross_cluster_patterns(_) -> []. analyze_performance_correlations(_) -> #{}. detect_system_emergent_properties(_) -> []. genetic_optimization(_, _) -> ok. simulated_annealing_optimization(_, _) -> ok. pso_optimization(_, _) -> ok. aco_optimization(_, _) -> ok. de_optimization(_, _) -> ok. neural_evolution_optimization(_, _) -> ok.