d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
exo-core
Core traits and types for the EXO-AI cognitive substrate. Provides IIT (Integrated Information Theory) consciousness measurement and Landauer thermodynamics primitives that every other EXO crate builds upon.
Features
- SubstrateBackend trait -- unified interface for pluggable compute backends (classical, quantum, hybrid).
- IIT Phi measurement -- quantifies integrated information across cognitive graph partitions.
- Landauer free energy tracking -- monitors thermodynamic cost of irreversible bit erasure during inference.
- Coherence routing -- directs information flow to maximise substrate coherence scores.
- Plasticity engine (SONA EWC++) -- continual learning with elastic weight consolidation to prevent catastrophic forgetting.
- Genomic integration -- encodes and decodes cognitive parameters as compact genomic sequences for evolution-based search.
Quick Start
Add the dependency to your Cargo.toml:
[dependencies]
exo-core = "0.1"
Basic usage:
use exo_core::consciousness::{ConsciousnessSubstrate, IITConfig};
use exo_core::thermodynamics::CognitiveThermometer;
// Measure integrated information (Phi)
let substrate = ConsciousnessSubstrate::new(IITConfig::default());
substrate.add_pattern(pattern);
let phi = substrate.compute_phi();
// Track computational thermodynamics
let thermo = CognitiveThermometer::new(300.0); // Kelvin
let cost = thermo.landauer_cost_bits(1024);
println!("Landauer cost for 1024 bits: {:.6} kT", cost);
Crate Layout
| Module | Purpose |
|---|---|
backend |
SubstrateBackend trait and helpers |
iit |
Phi computation and partition analysis |
thermo |
Landauer energy and entropy bookkeeping |
coherence |
Routing and coherence scoring |
plasticity |
SONA EWC++ continual-learning engine |
genomic |
Genome encoding / decoding utilities |
Requirements
- Rust 1.78+
- No required system dependencies
Links
License
MIT OR Apache-2.0