ruvector_consciousness/
traits.rs

1//! Trait hierarchy for consciousness computation engines.
2//!
3//! All Φ computation algorithms implement [`PhiEngine`]. Extension traits
4//! provide causal emergence and quantum-collapse integration.
5
6use crate::error::ConsciousnessError;
7use crate::types::{ComputeBudget, EmergenceResult, PhiAlgorithm, PhiResult, TransitionMatrix};
8
9/// Core trait for integrated information (Φ) computation.
10///
11/// Implementations must be thread-safe (`Send + Sync`) so they can be shared
12/// across parallel pipelines.
13pub trait PhiEngine: Send + Sync {
14    /// Compute Φ for the given transition probability matrix.
15    ///
16    /// The `state` parameter specifies the current system state as an index
17    /// into the TPM. If `None`, computes Φ over the stationary distribution.
18    fn compute_phi(
19        &self,
20        tpm: &TransitionMatrix,
21        state: Option<usize>,
22        budget: &ComputeBudget,
23    ) -> Result<PhiResult, ConsciousnessError>;
24
25    /// Return the algorithm identifier.
26    fn algorithm(&self) -> PhiAlgorithm;
27
28    /// Estimate computational cost without performing the computation.
29    fn estimate_cost(&self, n: usize) -> u64;
30}
31
32/// Extension trait for causal emergence computation.
33pub trait EmergenceEngine: Send + Sync {
34    /// Compute causal emergence for a system at multiple scales.
35    ///
36    /// Finds the coarse-graining of the micro-level TPM that maximizes
37    /// effective information, then computes the emergence metric.
38    fn compute_emergence(
39        &self,
40        tpm: &TransitionMatrix,
41        budget: &ComputeBudget,
42    ) -> Result<EmergenceResult, ConsciousnessError>;
43
44    /// Compute effective information for a given TPM.
45    fn effective_information(&self, tpm: &TransitionMatrix) -> Result<f64, ConsciousnessError>;
46}
47
48/// Trait for quantum-inspired consciousness collapse.
49///
50/// Integrates with `ruqu-exotic` quantum collapse search to model
51/// consciousness as a measurement-like collapse from superposition
52/// of possible partitions.
53pub trait ConsciousnessCollapse: Send + Sync {
54    /// Collapse the partition superposition to find the MIP.
55    ///
56    /// Instead of exhaustive enumeration, models partitions as amplitudes
57    /// and uses Grover-like iterations biased by information loss to
58    /// probabilistically find the minimum information partition.
59    fn collapse_to_mip(
60        &self,
61        tpm: &TransitionMatrix,
62        iterations: usize,
63        seed: u64,
64    ) -> Result<PhiResult, ConsciousnessError>;
65}
ruvector_consciousness/traits.rs

ruvector_consciousness/
traits.rs
