L2L
- Quickstart
- Overview
- API Reference
- Optimizees
- Optimizers
- Optimizer Base Module
- Implemented Examples
- Optimizer using Cross Entropy
- Optimizer using FACE
- Optimizer using Gradient Descent
- GradientDescentOptimizer
GradientDescentOptimizerGradientDescentOptimizer.post_process()GradientDescentOptimizer.end()GradientDescentOptimizer.init_classic_gd()GradientDescentOptimizer.init_rmsprop()GradientDescentOptimizer.init_adam()GradientDescentOptimizer.init_ada_max()GradientDescentOptimizer.init_stochastic_gd()GradientDescentOptimizer.classic_gd_update()GradientDescentOptimizer.rmsprop_update()GradientDescentOptimizer.adam_update()GradientDescentOptimizer.ada_max_update()GradientDescentOptimizer.stochastic_gd_update()
- ClassicGDParameters
- StochasticGDParameters
StochasticGDParametersStochasticGDParameters.exploration_step_sizeStochasticGDParameters.learning_rateStochasticGDParameters.n_iterationStochasticGDParameters.n_random_stepsStochasticGDParameters.seedStochasticGDParameters.stochastic_decayStochasticGDParameters.stochastic_deviationStochasticGDParameters.stop_criterion
- AdamParameters
- RMSPropParameters
- GradientDescentOptimizer
- Optimizer using Grid Search
- Optimizer using Evolutionary Algorithm
- GeneticAlgorithmOptimizer
- GeneticAlgorithmParameters
GeneticAlgorithmParametersGeneticAlgorithmParameters.cx_probGeneticAlgorithmParameters.ind_probGeneticAlgorithmParameters.mate_parGeneticAlgorithmParameters.mut_parGeneticAlgorithmParameters.mut_probGeneticAlgorithmParameters.n_iterationGeneticAlgorithmParameters.pop_sizeGeneticAlgorithmParameters.seedGeneticAlgorithmParameters.tourn_size
- Optimizer using Simulated Annealing
- Optimizer using Evolution Strategies
- EvolutionStrategiesOptimizer
- EvolutionStrategiesParameters
EvolutionStrategiesParametersEvolutionStrategiesParameters.fitness_shaping_enabledEvolutionStrategiesParameters.learning_rateEvolutionStrategiesParameters.mirrored_sampling_enabledEvolutionStrategiesParameters.n_iterationEvolutionStrategiesParameters.noise_stdEvolutionStrategiesParameters.pop_sizeEvolutionStrategiesParameters.seedEvolutionStrategiesParameters.stop_criterion
- Optimizer using Natural Evolution Strategies
- NaturalEvolutionStrategiesOptimizer
- NaturalEvolutionStrategiesParameters
NaturalEvolutionStrategiesParametersNaturalEvolutionStrategiesParameters.fitness_shaping_enabledNaturalEvolutionStrategiesParameters.learning_rate_muNaturalEvolutionStrategiesParameters.learning_rate_sigmaNaturalEvolutionStrategiesParameters.mirrored_sampling_enabledNaturalEvolutionStrategiesParameters.muNaturalEvolutionStrategiesParameters.n_iterationNaturalEvolutionStrategiesParameters.pop_sizeNaturalEvolutionStrategiesParameters.seedNaturalEvolutionStrategiesParameters.sigmaNaturalEvolutionStrategiesParameters.stop_criterion
- Simulation control
- Trajectory
- Individual
- ParamterGroup
- Environment
- Experiment
- Runner
RunnerRunner.collect_results_from_run()Runner.run()Runner.produce_run_command()Runner.launch_worker()Runner.launch_workers()Runner.close_workers()Runner.restart_worker()Runner.restart_individual()Runner.populate_free_workers()Runner.simulate_generation()Runner.prepare_run_file()Runner.dump_traj()Runner.create_zipfile()
- Logging Tools
- Other module functions
- L2L Experiments
- Indices and tables