"""
MLE — Morpho-Logic Engine
===========================
A novel reasoning AI architecture based on:
- 4096-bit binary hyperdimensional vectors
- Sparse distributed memory with Hamming distance proximity
- Circular convolution binding for semantic composition
- Energy-based dynamics for gradient-free reasoning
- SIMD-optimized CPU computation (bit-slicing + popcount)

Modules:
    memory   — Sparse Address Table with LSH indexing
    routing  — Recursive JIT Routing (beam search)
    binding  — Semantic binding via circular convolution & XOR
    energy   — Energy functions and relaxation dynamics
    inference — Full reasoning engine

Quick start:
    from mle import MorphoLogicEngine
    engine = MorphoLogicEngine()
    engine.add_concept("cat")
    engine.add_relation("cat", "is_a", "animal")
    result = engine.reason("cat")
"""

__version__ = "0.1.0"
__author__ = "MLE Team"

from .inference.reasoning_engine import ReasoningEngine as MorphoLogicEngine
from .memory import SparseAddressTable, HammingLSH
from .routing import RecursiveJITRouter, RoutingResult
from .binding import HRRBinding, BinaryBinding, BindingEngine
from .energy import EnergyFunction, RelaxationDynamics, HopfieldDynamics, EnergyModel

__all__ = [
    'MorphoLogicEngine',
    'SparseAddressTable', 'HammingLSH',
    'RecursiveJITRouter', 'RoutingResult',
    'HRRBinding', 'BinaryBinding', 'BindingEngine',
    'EnergyFunction', 'RelaxationDynamics', 'HopfieldDynamics', 'EnergyModel',
]