Module training 

FEAGI v1 Training API

Endpoints for training, reinforcement learning, and fitness evaluation Maps to Python: feagi/api/v1/training.py

Functions

delete_fitness_stats

Delete fitness statistics data.

delete_reset_fitness_stats

Reset fitness statistics to initial state.

get_brain_fitness

Get current brain fitness score for evolutionary evaluation.

get_fitness_criteria

Get fitness evaluation criteria used for brain assessment.

get_fitness_stats

Get fitness statistics including historical performance data.

get_shock_options

Get available shock/punishment options for training.

get_shock_status

Get current shock/punishment status and active scenarios.

get_stats

Get training statistics including episodes and rewards.

get_status

Get training system status including active state and current mode.

get_training_report

Get training progress report with performance metrics and insights.

post_config

Configure training parameters including learning rates and reward settings.

post_fitness_criteria

Set fitness evaluation criteria (alternative endpoint).

post_gameover

Signal game over condition for episode termination.

post_punishment

Apply punishment signal for negative reinforcement learning.

post_punishment_intensity

Set punishment intensity for negative reinforcement.

post_reward

Apply reward signal for positive reinforcement learning.

post_reward_intensity

Set reward intensity for positive reinforcement.

post_shock

Configure shock/punishment scenarios for reinforcement learning.

post_shock_activate

Activate shock/punishment scenario immediately.

put_fitness_criteria

Update fitness evaluation criteria for brain assessment.

put_fitness_stats

Update fitness statistics with new data.