Architecture

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Overview

Macula TWEANN uses a layered architecture with clear separation of concerns:

Module Dependencies

Layers

Core Data Layer

Modules: genotype, morphology

Handles persistent storage of neural network blueprints (genotypes) using Mnesia. Morphologies define problem-specific sensor and actuator configurations.

Network Components Layer

Modules: cortex, sensor, neuron, actuator

Process-based implementation of neural network elements. Each component runs as a separate Erlang process with message-passing communication.

Construction Layer

Modules: constructor, exoself

Constructs running phenotypes (process networks) from stored genotypes. The exoself acts as a coordinator for each agent's evaluation.

Evolution Layer

Modules: genome_mutator, crossover, selection_algorithm

Implements genetic operators for topology and weight evolution. Supports both asexual (mutation) and sexual (crossover) reproduction.

Population Layer

Modules: population_monitor, species_identifier, fitness_postprocessor

Manages multi-agent evolution with speciation for diversity preservation and multi-objective fitness evaluation.

Utilities Layer

Modules: tweann_logger, functions, signal_aggregator, perturbation_utils, selection_utils

Helper functions for logging, activation functions, signal processing, weight perturbation, and selection algorithms.

Process Hierarchy

Supervision Tree

The process tree uses spawn_link for crash propagation:

  • population_monitor (gen_server) manages multiple agents
  • Each agent has an exoself coordinating its network
  • Network processes (cortex, sensors, neurons, actuators) are linked
  • Crashes propagate up, terminating the entire network evaluation

Evaluation Flow

Evaluation Cycle

The sense-think-act cycle:

  1. Sense: Cortex triggers sensors, which read from environment
  2. Think: Neurons receive signals, aggregate, and activate
  3. Act: Actuators collect outputs and interact with environment
  4. Fitness is computed and reported back to exoself

Safety Features

Timeouts

  • Cortex: 30s sync timeout (configurable)
  • Neuron: 10s input timeout (configurable)

Prevents infinite hangs if network components fail to respond.

Crash Handling

All network processes use spawn_link:

  • Component crashes terminate the entire network
  • Exoself reports failure to population monitor
  • Clean shutdown with proper resource cleanup

Data Flow

Genotype (Mnesia)
    ↓ construct
Phenotype (Processes)
    ↓ evaluate
Fitness
    ↓ selection
Survivors
    ↓ mutation/crossover
New Genotypes

Next Steps

  • See module documentation for detailed API reference
  • Check Quick Start for usage examples