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Evolution Simulation System Documentation

Overview

The Evolution Simulation is a complex ecosystem simulation built in Rust using an Entity-Component-System (ECS) architecture. It simulates the evolution of entities through natural selection, genetic inheritance, and environmental pressures.

Core Architecture

Technology Stack

  • Language: Rust
  • ECS Framework: Hecs
  • Parallelism: Rayon
  • Rendering: WGPU (Desktop) / WebGL/WGPU (Web via wgpu)
  • Serialization: Serde

Design Principles

  • Modularity: Systems (Movement, Interaction, Energy, Reproduction) are independent.
  • Parallel processing: Heavy computations use rayon for multi-core scaling.
  • Configurability: Simulation parameters are hot-swappable via JSON.

System Components

1. Entity Components

Core data structures managed by the ECS:

  • Position & Velocity: 2D Physics vectors.
  • Energy: Life force; entities die at 0 energy.
  • Size: Radius affecting energy cost and interaction range.
  • Color: Visual phenotype derived from genes.
  • Genes: The genetic blueprint (see below).

2. Genetic System

Genes determine all behavior and attributes. They are mutable and heritable.

Category Traits
Movement speed, sense_radius
Energy efficiency, loss_rate, gain_rate, size_factor
Reproduction rate, mutation_rate
Shape/Color hue, saturation
Behavior movement_style, social_tendency, gene_preference

3. Movement System

Entities exhibit one of five genetically determined movement styles:

  1. Random: Baseline brownian-like motion.
  2. Flocking: Cohesion, alignment, and separation (Boids algorithm) with genetically similar neighbors.
  3. Solitary: Active avoidance of other entities.
  4. Predatory: Active pursuit of prey based on genetic preference and size advantage.
  5. Grazing: Slow, steady movement with minimal energy expenditure.

4. Interaction System

  • Predation: Larger entities eat smaller specific prey.
  • Gene Preference: Predators prefer genetically distinct prey (promoting diversity).
  • Energy Transfer: Eating yields energy; movement and existence consume it.

5. Spatial System

  • Spatial Grid: The world is partitioned into cells to optimize neighbor lookups (O(1) instead of O(N²)).
  • Boundaries: Soft boundaries with increasing "center pressure" to keep populations active.

Statistics

Real-time metrics tracking:

  • Population counts by species/behavior.
  • Average genetic drift (evolution speed).
  • System performance (FPS, step time).

Roadmap & Future Ideas

  • Environmental Complexity: Terrain, obstacles, and localized resource patches.
  • Advanced Biology: Aging, disease/parasites, and sexual dimorphism.
  • Complex Sociality: Mating rituals, territorial defense, and memory/learning.
  • Multi-Species: Symbiotic relationships and food webs.