# AdaEvolve - Adaptive Evolutionary Search Configuration
#
# AdaEvolve is an adaptive multi-island evolutionary algorithm that adjusts
# search intensity per island based on accumulated improvement history.
#
# Key features:
#   - Per-island adaptive exploration/exploitation via accumulated signal (G)
#   - UCB with decayed magnitude rewards for island selection
#   - UnifiedArchive per island for quality-diversity balance
#   - Ring migration for cross-pollination between islands
#   - Dynamic island spawning when global productivity drops
#   - Paradigm breakthrough for high-level strategy shifts during stagnation
#
# Usage:
#   Copy this file to your example directory as config_adaevolve.yaml
#   and fill in the system_message with your problem description.

# General settings
max_iterations: 100
checkpoint_interval: 10
log_level: "INFO"
random_seed: 42

# LLM configuration
llm:
  models:
    - name: "gpt-5"
      weight: 1.0
  api_base: "https://api.openai.com/v1"
  temperature: 0.7
  # top_p: 0.95  # omitted by default; some providers (e.g. Anthropic) reject both temperature and top_p
  max_tokens: 32000
  timeout: 600
  # To use Gemini: comment out models + api_base above, uncomment below
  # models:
  #   - name: "gemini-3-pro-preview"
  # api_base: "https://generativelanguage.googleapis.com/v1beta/openai/"
  # api_key: ${GEMINI_API_KEY}

# Search configuration
search:
  type: "adaevolve"
  num_context_programs: 4
  database:
    # Population settings
    population_size: 20
    num_islands: 2

    # --- Adaptive search intensity ---
    # Controls how search intensity adapts based on improvement signal (G)
    # High G (productive island) -> low intensity (exploit)
    # Low G (stagnating island) -> high intensity (explore)
    decay: 0.9                        # Exponential moving average weight (rho)
    intensity_min: 0.15               # Minimum search intensity (exploitation)
    intensity_max: 0.5                # Maximum search intensity (exploration)

    # --- Ablation flags ---
    # Set to false to disable specific adaptive mechanisms for ablation studies
    use_adaptive_search: true         # G-based intensity vs fixed_intensity
    use_ucb_selection: true           # UCB island selection vs round-robin
    use_migration: true               # Inter-island migration
    use_unified_archive: true         # Quality-diversity archive vs simple list
    # fixed_intensity: 0.4            # Used when use_adaptive_search=false

    # --- Migration ---
    migration_interval: 15            # Migrate every N iterations
    migration_count: 5                # Number of top programs to migrate

    # --- Archive settings (when use_unified_archive=true) ---
    fitness_weight: 1.0               # Weight for fitness rank in elite score
    novelty_weight: 0.0               # Weight for novelty rank in elite score
    diversity_strategy: "code"        # Diversity metric: "code", "metric", or "hybrid"

    # --- Optional Pareto multiobjective mode ---
    # Leave pareto_objectives empty to keep the current scalar combined_score behavior.
    # When enabled, return the raw objective metrics from the evaluator and set:
    # pareto_objectives:
    #   - accuracy
    #   - latency
    # higher_is_better:
    #   accuracy: true
    #   latency: false
    # fitness_key: accuracy              # Optional scalar proxy for adaptive state / tie-breaking
    # pareto_objectives_weight: 0.4      # Weight of Pareto percentile in archive elite score

    # --- Dynamic island spawning ---
    use_dynamic_islands: true
    max_islands: 5                    # Maximum number of islands
    spawn_productivity_threshold: 0.015  # Spawn if global productivity below this
    spawn_cooldown_iterations: 30     # Wait N iterations between spawns

    # --- Paradigm breakthrough ---
    use_paradigm_breakthrough: true
    paradigm_window_size: 10          # Window for improvement rate calculation
    paradigm_improvement_threshold: 0.12  # Stagnation threshold
    paradigm_max_uses: 2              # Max uses per paradigm
    paradigm_max_tried: 10            # Max tried paradigms to track
    paradigm_num_to_generate: 3       # Number of paradigms to generate per trigger

    # --- Error retry ---
    enable_error_retry: true
    max_error_retries: 2

# Prompt configuration
prompt:
  system_message: |
    <REPLACE WITH YOUR PROBLEM-SPECIFIC SYSTEM MESSAGE>

    Describe:
    - What the algorithm/function should do
    - Input/output format
    - Optimization objective and metrics
    - Constraints
    - Techniques to explore

# Evaluator configuration
evaluator:
  timeout: 360
  max_retries: 3
  cascade_evaluation: true
  cascade_thresholds: [0.3, 0.6]

# Generation settings
diff_based_generation: true
max_solution_length: 60000