scirs2-metrics 0.3.2

//! Consciousness simulation module for neuromorphic systems
//!
//! This module implements consciousness theories including Global Workspace Theory,
//! Integrated Information Theory, and attention systems.

#![allow(clippy::too_many_arguments)]
#![allow(dead_code)]

use crate::error::Result;
use scirs2_core::numeric::Float;
use std::collections::HashMap;

/// Consciousness simulation module
#[derive(Debug)]
pub struct ConsciousnessSimulator<F: Float> {
    /// Global workspace theory implementation
    pub global_workspace: GlobalWorkspaceTheory<F>,
    /// Integrated information theory
    pub integrated_information: IntegratedInformationTheory<F>,
    /// Attention mechanisms
    pub attention_systems: AttentionSystems<F>,
    /// Self-awareness modules
    pub self_awareness: SelfAwarenessModule<F>,
    /// Higher-order thought processes
    pub higher_order_thoughts: HigherOrderThoughtSystem<F>,
}

/// Global Workspace Theory implementation
#[derive(Debug)]
pub struct GlobalWorkspaceTheory<F: Float> {
    /// Global workspace neural architecture
    pub global_workspace: GlobalWorkspace<F>,
    /// Competition mechanisms for consciousness
    pub competition_mechanisms: Vec<ConsciousnessCompetition<F>>,
    /// Broadcasting protocols
    pub broadcasting_protocols: Vec<BroadcastingProtocol<F>>,
    /// Access consciousness vs phenomenal consciousness
    pub consciousness_types: ConsciousnessTypes<F>,
}

/// Global workspace for conscious processing
#[derive(Debug)]
pub struct GlobalWorkspace<F: Float> {
    /// Current global workspace contents
    pub contents: Vec<WorkspaceContent<F>>,
    /// Workspace capacity
    pub capacity: usize,
    /// Competition threshold
    pub competition_threshold: F,
    /// Broadcasting strength
    pub broadcasting_strength: F,
}

/// Content in the global workspace
#[derive(Debug)]
pub struct WorkspaceContent<F: Float> {
    /// Content representation
    pub representation: Vec<F>,
    /// Activation strength
    pub activation: F,
    /// Source module
    pub source: String,
    /// Content type
    pub content_type: ContentType,
    /// Time in workspace
    pub duration: u64,
}

/// Types of content in workspace
#[derive(Debug, Clone)]
pub enum ContentType {
    /// Sensory information
    Sensory(String),
    /// Memory recall
    Memory,
    /// Goal/intention
    Goal,
    /// Emotional state
    Emotion,
    /// Abstract concept
    Concept,
}

/// Competition mechanisms for consciousness
#[derive(Debug)]
pub struct ConsciousnessCompetition<F: Float> {
    /// Competition type
    pub competition_type: String,
    /// Competition parameters
    pub parameters: HashMap<String, F>,
    /// Winner-take-all threshold
    pub winner_threshold: F,
}

/// Broadcasting protocol for global workspace
#[derive(Debug)]
pub struct BroadcastingProtocol<F: Float> {
    /// Protocol type
    pub protocol_type: String,
    /// Broadcasting range
    pub range: Vec<String>,
    /// Broadcasting strength
    pub strength: F,
}

/// Types of consciousness
#[derive(Debug)]
pub struct ConsciousnessTypes<F: Float> {
    /// Access consciousness level
    pub access_consciousness: F,
    /// Phenomenal consciousness level
    pub phenomenal_consciousness: F,
    /// Self-consciousness level
    pub self_consciousness: F,
}

/// Integrated Information Theory implementation
#[derive(Debug)]
pub struct IntegratedInformationTheory<F: Float> {
    /// Phi calculation algorithms
    pub phi_calculators: Vec<PhiCalculationAlgorithm<F>>,
    /// Information integration measures
    pub integration_measures: Vec<InformationIntegrationMeasure<F>>,
    /// Consciousness quantification
    pub consciousness_quantifiers: Vec<ConsciousnessQuantifier<F>>,
    /// Causal structure analysis
    pub causal_analyzers: Vec<CausalStructureAnalyzer<F>>,
}

/// Phi calculation algorithm for IIT
#[derive(Debug)]
pub struct PhiCalculationAlgorithm<F: Float> {
    /// Algorithm type
    pub algorithm_type: String,
    /// Current phi value
    pub current_phi: F,
    /// Computation parameters
    pub parameters: HashMap<String, F>,
}

/// Information integration measure
#[derive(Debug)]
pub struct InformationIntegrationMeasure<F: Float> {
    /// Measure type
    pub measure_type: String,
    /// Integration value
    pub integration_value: F,
    /// Measurement parameters
    pub parameters: HashMap<String, F>,
}

/// Consciousness quantifier
#[derive(Debug)]
pub struct ConsciousnessQuantifier<F: Float> {
    /// Quantification method
    pub method: String,
    /// Consciousness level
    pub consciousness_level: F,
    /// Confidence in measurement
    pub confidence: F,
}

/// Causal structure analyzer
#[derive(Debug)]
pub struct CausalStructureAnalyzer<F: Float> {
    /// Analysis method
    pub method: String,
    /// Causal relationships
    pub causal_relationships: HashMap<String, Vec<(String, F)>>,
    /// Causal strength threshold
    pub threshold: F,
}

/// Attention systems for consciousness
#[derive(Debug)]
pub struct AttentionSystems<F: Float> {
    /// Bottom-up attention
    pub bottom_up: BottomUpAttention<F>,
    /// Top-down attention
    pub top_down: TopDownAttention<F>,
    /// Executive attention
    pub executive: ExecutiveAttention<F>,
    /// Sustained attention
    pub sustained: SustainedAttention<F>,
}

/// Bottom-up attention system
#[derive(Debug)]
pub struct BottomUpAttention<F: Float> {
    /// Saliency map
    pub saliency_map: Vec<F>,
    /// Attention weights
    pub attention_weights: Vec<F>,
    /// Detection threshold
    pub threshold: F,
}

/// Top-down attention system
#[derive(Debug)]
pub struct TopDownAttention<F: Float> {
    /// Goal-driven attention weights
    pub goal_weights: HashMap<String, F>,
    /// Expectation-based attention
    pub expectation_weights: Vec<F>,
    /// Control parameters
    pub control_parameters: HashMap<String, F>,
}

/// Executive attention system
#[derive(Debug)]
pub struct ExecutiveAttention<F: Float> {
    /// Conflict monitoring
    pub conflict_monitor: ConflictMonitor<F>,
    /// Cognitive control
    pub cognitive_control: CognitiveControl<F>,
    /// Task switching
    pub task_switcher: TaskSwitcher<F>,
}

/// Conflict monitoring system
#[derive(Debug)]
pub struct ConflictMonitor<F: Float> {
    /// Conflict detection threshold
    pub threshold: F,
    /// Current conflict level
    pub current_conflict: F,
    /// Conflict history
    pub conflict_history: Vec<F>,
}

/// Cognitive control system
#[derive(Debug)]
pub struct CognitiveControl<F: Float> {
    /// Control strength
    pub control_strength: F,
    /// Control parameters
    pub parameters: HashMap<String, F>,
    /// Active control signals
    pub active_signals: Vec<F>,
}

/// Task switching system
#[derive(Debug)]
pub struct TaskSwitcher<F: Float> {
    /// Current task
    pub current_task: String,
    /// Task queue
    pub task_queue: Vec<String>,
    /// Switching cost
    pub switching_cost: F,
}

/// Sustained attention system
#[derive(Debug)]
pub struct SustainedAttention<F: Float> {
    /// Attention duration
    pub attention_duration: u64,
    /// Vigilance level
    pub vigilance_level: F,
    /// Fatigue parameters
    pub fatigue_parameters: HashMap<String, F>,
}

/// Self-awareness module
#[derive(Debug)]
pub struct SelfAwarenessModule<F: Float> {
    /// Self-model
    pub self_model: SelfModel<F>,
    /// Metacognition system
    pub metacognition: MetacognitionSystem<F>,
    /// Theory of mind
    pub theory_of_mind: TheoryOfMind<F>,
}

/// Self-model for self-awareness
#[derive(Debug)]
pub struct SelfModel<F: Float> {
    /// Self-representation
    pub representation: Vec<F>,
    /// Self-knowledge
    pub knowledge: HashMap<String, F>,
    /// Self-evaluation
    pub evaluation_metrics: HashMap<String, F>,
}

/// Metacognition system
#[derive(Debug)]
pub struct MetacognitionSystem<F: Float> {
    /// Metacognitive knowledge
    pub knowledge: MetacognitiveKnowledge<F>,
    /// Metacognitive regulation
    pub regulation: MetacognitiveRegulation<F>,
    /// Metamemory
    pub metamemory: Metamemory<F>,
}

/// Metacognitive knowledge
#[derive(Debug)]
pub struct MetacognitiveKnowledge<F: Float> {
    /// Knowledge about strategies
    pub strategy_knowledge: HashMap<String, F>,
    /// Knowledge about tasks
    pub task_knowledge: HashMap<String, F>,
    /// Knowledge about self
    pub self_knowledge: HashMap<String, F>,
}

/// Metacognitive regulation
#[derive(Debug)]
pub struct MetacognitiveRegulation<F: Float> {
    /// Planning strategies
    pub planning: HashMap<String, F>,
    /// Monitoring strategies
    pub monitoring: HashMap<String, F>,
    /// Evaluation strategies
    pub evaluation: HashMap<String, F>,
}

/// Metamemory system
#[derive(Debug)]
pub struct Metamemory<F: Float> {
    /// Memory confidence
    pub confidence: HashMap<String, F>,
    /// Memory accuracy predictions
    pub accuracy_predictions: HashMap<String, F>,
    /// Memory strategies
    pub strategies: Vec<String>,
}

/// Theory of mind
#[derive(Debug)]
pub struct TheoryOfMind<F: Float> {
    /// Mental state models
    pub mental_state_models: HashMap<String, MentalStateModel<F>>,
    /// Belief tracking
    pub belief_tracker: BeliefTracker<F>,
    /// Intention recognition
    pub intention_recognizer: IntentionRecognizer<F>,
}

/// Mental state model for theory of mind
#[derive(Debug)]
pub struct MentalStateModel<F: Float> {
    /// Agent identifier
    pub agent_id: String,
    /// Beliefs
    pub beliefs: HashMap<String, F>,
    /// Desires
    pub desires: HashMap<String, F>,
    /// Intentions
    pub intentions: HashMap<String, F>,
}

/// Belief tracking system
#[derive(Debug)]
pub struct BeliefTracker<F: Float> {
    /// Current beliefs
    pub beliefs: HashMap<String, F>,
    /// Belief confidence
    pub confidence: HashMap<String, F>,
    /// Belief update rules
    pub update_rules: Vec<String>,
}

/// Intention recognition system
#[derive(Debug)]
pub struct IntentionRecognizer<F: Float> {
    /// Recognition algorithms
    pub algorithms: Vec<String>,
    /// Current intentions
    pub current_intentions: HashMap<String, F>,
    /// Intention confidence
    pub confidence: HashMap<String, F>,
}

/// Higher-order thought system
#[derive(Debug)]
pub struct HigherOrderThoughtSystem<F: Float> {
    /// Higher-order thoughts
    pub higher_order_thoughts: Vec<HigherOrderThought<F>>,
    /// Thought monitoring
    pub thought_monitor: ThoughtMonitor<F>,
    /// Recursive thinking
    pub recursive_thinker: RecursiveThinking<F>,
}

/// Higher-order thought
#[derive(Debug)]
pub struct HigherOrderThought<F: Float> {
    /// Thought content
    pub content: Vec<F>,
    /// Thought about thought
    pub meta_content: Vec<F>,
    /// Recursion level
    pub recursion_level: usize,
}

/// Thought monitoring system
#[derive(Debug)]
pub struct ThoughtMonitor<F: Float> {
    /// Monitored thoughts
    pub monitored_thoughts: Vec<String>,
    /// Monitoring strength
    pub monitoring_strength: F,
    /// Thought patterns
    pub patterns: HashMap<String, F>,
}

/// Recursive thinking system
#[derive(Debug)]
pub struct RecursiveThinking<F: Float> {
    /// Maximum recursion depth
    pub max_depth: usize,
    /// Current depth
    pub current_depth: usize,
    /// Recursion parameters
    pub parameters: HashMap<String, F>,
}

impl<F: Float> ConsciousnessSimulator<F> {
    /// Create new consciousness simulator
    pub fn new() -> Result<Self> {
        Ok(Self {
            global_workspace: GlobalWorkspaceTheory::new()?,
            integrated_information: IntegratedInformationTheory::new()?,
            attention_systems: AttentionSystems::new()?,
            self_awareness: SelfAwarenessModule::new(),
            higher_order_thoughts: HigherOrderThoughtSystem::new(),
        })
    }

    /// Simulate conscious processing
    pub fn simulate_consciousness(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Process through global workspace
        let workspace_output = self.global_workspace.process(input)?;

        // Calculate integrated information
        let phi = self
            .integrated_information
            .calculate_phi(&workspace_output)?;

        // Apply attention mechanisms
        let attended_output = self.attention_systems.apply_attention(&workspace_output)?;

        // Self-awareness processing
        let self_aware_output = self.self_awareness.process(&attended_output)?;

        // Higher-order thought processing
        let final_output = self.higher_order_thoughts.process(&self_aware_output)?;

        Ok(final_output)
    }

    /// Get consciousness level
    pub fn get_consciousness_level(&self) -> F {
        // Simplified consciousness quantification
        let workspace_activity = self.global_workspace.get_activity_level();
        let phi_value = self.integrated_information.get_current_phi();
        let attention_strength = self.attention_systems.get_attention_strength();

        // Combine measures for overall consciousness level
        (workspace_activity + phi_value + attention_strength)
            / F::from(3.0).expect("Failed to convert constant to float")
    }
}

impl<F: Float> GlobalWorkspaceTheory<F> {
    /// Create new global workspace theory implementation
    pub fn new() -> Result<Self> {
        Ok(Self {
            global_workspace: GlobalWorkspace::new(),
            competition_mechanisms: Vec::new(),
            broadcasting_protocols: Vec::new(),
            consciousness_types: ConsciousnessTypes::new(),
        })
    }

    /// Process input through global workspace
    pub fn process(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Add input to workspace as content
        self.global_workspace
            .add_content(input, "input".to_string())?;

        // Run competition mechanisms
        self.run_competition()?;

        // Broadcast winning content
        let output = self.broadcast_content()?;

        Ok(output)
    }

    /// Run competition in global workspace
    fn run_competition(&mut self) -> Result<()> {
        // Simplified competition: keep strongest activations
        self.global_workspace.contents.sort_by(|a, b| {
            b.activation
                .partial_cmp(&a.activation)
                .unwrap_or(std::cmp::Ordering::Equal)
        });

        // Keep only top contents within capacity
        self.global_workspace
            .contents
            .truncate(self.global_workspace.capacity);

        Ok(())
    }

    /// Broadcast content from workspace
    fn broadcast_content(&self) -> Result<Vec<F>> {
        // Combine all content representations
        let mut output = Vec::new();
        for content in &self.global_workspace.contents {
            output.extend_from_slice(&content.representation);
        }
        Ok(output)
    }

    /// Get activity level
    pub fn get_activity_level(&self) -> F {
        if self.global_workspace.contents.is_empty() {
            F::zero()
        } else {
            self.global_workspace
                .contents
                .iter()
                .map(|c| c.activation)
                .fold(F::zero(), |acc, x| acc + x)
                / F::from(self.global_workspace.contents.len()).expect("Operation failed")
        }
    }
}

impl<F: Float> GlobalWorkspace<F> {
    /// Create new global workspace
    pub fn new() -> Self {
        Self {
            contents: Vec::new(),
            capacity: 7, // Miller's magic number
            competition_threshold: F::from(0.5).expect("Failed to convert constant to float"),
            broadcasting_strength: F::from(1.0).expect("Failed to convert constant to float"),
        }
    }

    /// Add content to workspace
    pub fn add_content(&mut self, representation: &[F], source: String) -> Result<()> {
        let content = WorkspaceContent {
            representation: representation.to_vec(),
            activation: F::from(0.8).expect("Failed to convert constant to float"), // Default activation
            source,
            content_type: ContentType::Sensory("visual".to_string()),
            duration: 0,
        };

        self.contents.push(content);
        Ok(())
    }
}

impl<F: Float> IntegratedInformationTheory<F> {
    /// Create new IIT implementation
    pub fn new() -> Result<Self> {
        Ok(Self {
            phi_calculators: Vec::new(),
            integration_measures: Vec::new(),
            consciousness_quantifiers: Vec::new(),
            causal_analyzers: Vec::new(),
        })
    }

    /// Calculate phi (integrated information)
    pub fn calculate_phi(&self, _input: &[F]) -> Result<F> {
        // Simplified phi calculation
        // In practice, this would involve complex computations
        // of information integration across the system
        Ok(F::from(0.3).expect("Failed to convert constant to float"))
    }

    /// Get current phi value
    pub fn get_current_phi(&self) -> F {
        F::from(0.3).expect("Failed to convert constant to float") // Simplified
    }
}

impl<F: Float> AttentionSystems<F> {
    /// Create new attention systems
    pub fn new() -> Result<Self> {
        Ok(Self {
            bottom_up: BottomUpAttention::new(),
            top_down: TopDownAttention::new(),
            executive: ExecutiveAttention::new(),
            sustained: SustainedAttention::new(),
        })
    }

    /// Apply attention mechanisms
    pub fn apply_attention(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Apply bottom-up attention
        let bottom_up_attended = self.bottom_up.apply(input)?;

        // Apply top-down attention
        let top_down_attended = self.top_down.apply(&bottom_up_attended)?;

        // Apply executive attention
        let executive_attended = self.executive.apply(&top_down_attended)?;

        // Apply sustained attention
        let final_attended = self.sustained.apply(&executive_attended)?;

        Ok(final_attended)
    }

    /// Get attention strength
    pub fn get_attention_strength(&self) -> F {
        F::from(0.7).expect("Failed to convert constant to float") // Simplified
    }
}

// Placeholder implementations for supporting types
impl<F: Float> ConsciousnessTypes<F> {
    pub fn new() -> Self {
        Self {
            access_consciousness: F::zero(),
            phenomenal_consciousness: F::zero(),
            self_consciousness: F::zero(),
        }
    }
}

impl<F: Float> SelfAwarenessModule<F> {
    pub fn new() -> Self {
        Self {
            self_model: SelfModel {
                representation: Vec::new(),
                knowledge: HashMap::new(),
                evaluation_metrics: HashMap::new(),
            },
            metacognition: MetacognitionSystem {
                knowledge: MetacognitiveKnowledge {
                    task_knowledge: HashMap::new(),
                    strategy_knowledge: HashMap::new(),
                    self_knowledge: HashMap::new(),
                },
                regulation: MetacognitiveRegulation {
                    planning: HashMap::new(),
                    monitoring: HashMap::new(),
                    evaluation: HashMap::new(),
                },
                metamemory: Metamemory {
                    confidence: HashMap::new(),
                    accuracy_predictions: HashMap::new(),
                    strategies: Vec::new(),
                },
            },
            theory_of_mind: TheoryOfMind {
                mental_state_models: HashMap::new(),
                belief_tracker: BeliefTracker {
                    beliefs: HashMap::new(),
                    confidence: HashMap::new(),
                    update_rules: Vec::new(),
                },
                intention_recognizer: IntentionRecognizer {
                    algorithms: Vec::new(),
                    current_intentions: HashMap::new(),
                    confidence: HashMap::new(),
                },
            },
        }
    }
}

impl<F: Float> HigherOrderThoughtSystem<F> {
    pub fn new() -> Self {
        Self {
            higher_order_thoughts: Vec::new(),
            thought_monitor: ThoughtMonitor {
                monitored_thoughts: Vec::new(),
                monitoring_strength: F::from(0.5).expect("Failed to convert constant to float"),
                patterns: HashMap::new(),
            },
            recursive_thinker: RecursiveThinking {
                current_depth: 0,
                parameters: HashMap::new(),
                max_depth: 5,
            },
        }
    }
}

// Specific implementations for complex types
impl<F: Float> BottomUpAttention<F> {
    pub fn new() -> Self {
        Self {
            saliency_map: Vec::new(),
            attention_weights: Vec::new(),
            threshold: F::from(0.5).expect("Failed to convert constant to float"),
        }
    }

    pub fn apply(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Simplified bottom-up attention
        Ok(input.to_vec())
    }
}

impl<F: Float> TopDownAttention<F> {
    pub fn new() -> Self {
        Self {
            goal_weights: HashMap::new(),
            expectation_weights: Vec::new(),
            control_parameters: HashMap::new(),
        }
    }

    pub fn apply(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Simplified top-down attention
        Ok(input.to_vec())
    }
}

impl<F: Float> ExecutiveAttention<F> {
    pub fn new() -> Self {
        Self {
            conflict_monitor: ConflictMonitor::new(),
            cognitive_control: CognitiveControl::new(),
            task_switcher: TaskSwitcher::new(),
        }
    }

    pub fn apply(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Simplified executive attention
        Ok(input.to_vec())
    }
}

impl<F: Float> SustainedAttention<F> {
    pub fn new() -> Self {
        Self {
            attention_duration: 0,
            vigilance_level: F::from(0.8).expect("Failed to convert constant to float"),
            fatigue_parameters: HashMap::new(),
        }
    }

    pub fn apply(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Simplified sustained attention
        Ok(input.to_vec())
    }
}

impl<F: Float> ConflictMonitor<F> {
    pub fn new() -> Self {
        Self {
            threshold: F::from(0.5).expect("Failed to convert constant to float"),
            current_conflict: F::zero(),
            conflict_history: Vec::new(),
        }
    }
}

impl<F: Float> CognitiveControl<F> {
    pub fn new() -> Self {
        Self {
            control_strength: F::from(0.7).expect("Failed to convert constant to float"),
            parameters: HashMap::new(),
            active_signals: Vec::new(),
        }
    }
}

impl<F: Float> TaskSwitcher<F> {
    pub fn new() -> Self {
        Self {
            current_task: "default".to_string(),
            task_queue: Vec::new(),
            switching_cost: F::from(0.1).expect("Failed to convert constant to float"),
        }
    }
}

impl<F: Float> SelfAwarenessModule<F> {
    /// Process through self-awareness
    pub fn process(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Simplified self-awareness processing
        Ok(input.to_vec())
    }
}

impl<F: Float> HigherOrderThoughtSystem<F> {
    /// Process through higher-order thoughts
    pub fn process(&mut self, input: &[F]) -> Result<Vec<F>> {
        // Simplified higher-order thought processing
        Ok(input.to_vec())
    }
}