agents

%% 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.