zenigame-batch-ga

Automate sequential GA batch executions by orchestrating multiple experiment runs with fixed arguments and calibration gates to rapidly establish baseline distributions. The framework handles end-to-end orchestration, progress tracking, and error handling via dedicated scripts and state files.

Interrupted GA batch runs can be resumed using the batch_state.json file. This state file tracks progress across execution iterations, allowing the orchestration process to recover and continue from the last completed run without losing collected metrics.

Compare per-run metrics across multiple genetic algorithm experiments by utilizing the automated report generation feature. The script extracts metrics from each individual run and compiles them into a report, making distribution comparison and baseline analysis straightforward.

The GA batch orchestration supports calibration steps between experiment runs. Sequential executions are gated by calibration checks, ensuring that each run meets specified calibration criteria before proceeding to the next iteration.

Control run arguments for repeated genetic algorithm experiments by configuring fixed parameters within the batch orchestration script. This ensures consistent argument application across all sequential executions for reliable baseline distribution generation.

Multiple GA iterations are needed to establish a baseline distribution because single runs exhibit stochastic variance. Sequential batch execution captures per-run metrics across multiple experiments, delivering the statistical distribution required for a reliable performance baseline.