config.yaml

# This file contains all configurable parameters for the HGM system.

# Language Model Configuration
llm:
  # Model used for self-improvement tasks
  self_improve_llm: "gpt-5-mini"
  
  # Model used for downstream evaluation tasks
  downstream_llm: "gpt-5-mini"
  
  # Model used for problem diagnosis
  diagnose_llm: "gpt-5-mini"

# Optimization Algorithm Parameters
optimization:
  # Alpha parameter for node expansion (controls exploration vs exploitation)
  alpha: 0.6
  
  # Beta parameter for cooling down factor
  beta: 1.0
  
  # Whether to use decreasing temperature over iterations
  cool_down: false
  
  # Randomness level for evaluation task selection (0.0 = deterministic, 1.0 = fully random)
  eval_random_level: 1.0
  
  # Number of pseudo descendant evaluations for tree search
  n_pseudo_descendant_evals: 10000

# Execution and Resource Management
execution:
  # Number of parallel workers for self-improvement attempts
  max_workers: 20
  
  # Timeout for self-improvement attempts (in seconds)
  self_improve_timeout: 3600  # 1 hour
  
  # Timeout for evaluation attempts (in seconds)
  evaluation_timeout: 3600   # 1 hour
  
  # Maximum number of task evaluations (evolution iterations)
  max_task_evals: 800

# Evaluation Settings
evaluation:
  # Skip full evaluation on SWE-bench if node is top N performing
  full_eval: false
  
  # Use Polyglot benchmark instead of SWE-bench
  polyglot: false

# Path Configuration
paths:
  # Output directory for results (if null, will be auto-generated)
  output_dir: "output_hgm:"
  
  # Directory to continue a previous run from
  continue_from: null
  
  # Name of the initial agent (required)
  initial_agent_name: "default_agent"