llamda.ga.mcts package

Submodules

llamda.ga.mcts.evolution module

llamda.ga.mcts.evolution_interface module

class llamda.ga.mcts.evolution_interface.InterfaceEC(m, problem, evaluator, llm_client, output_dir)

Bases: object

Parameters:

• m (int)

• problem (EohProblem)

• evaluator (Evaluator)

• llm_client (BaseClient)

• output_dir (str)

check_duplicate(population, code)

Parameters:

• population (list[MCTSIndividual])

• code (str)

Return type:

bool

check_duplicate_obj(population, obj)

Parameters:

• population (list[MCTSIndividual])

• obj (float)

Return type:

bool

evolve_algorithm(eval_times, pop, node, operator, name)

Parameters:

• eval_times (int)

• pop (list[MCTSIndividual])

• node (MCTSIndividual)

• operator (MCTSOperator)

• name (str)

Return type:

tuple[int, MCTSIndividual | None]

get_algorithm(pop, operator, name)

Parameters:

• pop (list[MCTSIndividual])

• operator (MCTSOperator)

• name (str)

Return type:

tuple[int, list[MCTSIndividual], MCTSIndividual]

get_offspring(pop, operator, name, father=None)

Parameters:

• pop (list[MCTSIndividual])

• operator (MCTSOperator)

• name (str)

• father (MCTSIndividual | None)

Return type:

tuple[list[MCTSIndividual], MCTSIndividual]

llamda.ga.mcts.evolution_interface.select_parents(pop, m)

Parameters:

• pop (list[MCTSIndividual])

• m (int)

Return type:

list[MCTSIndividual]

llamda.ga.mcts.evolution_interface.select_parents_e1(pop, m)

Parameters:

• pop (list[MCTSIndividual])

• m (int)

Return type:

list[MCTSIndividual]

llamda.ga.mcts.mcts module

class llamda.ga.mcts.mcts.MCTS(root_answer)

Bases: object

Parameters:

root_answer (str)

backpropagate(node)

Parameters:

node (MCTSNode)

Return type:

None

is_fully_expanded(node)

Parameters:

node (MCTSNode)

Return type:

bool

uct(node, eval_remain)

Parameters:

• node (MCTSNode)

• eval_remain (float)

Return type:

float

class llamda.ga.mcts.mcts.MCTSNode(algorithm, code, obj, depth=0, parent=None, visit=0, raw_info=None, Q=0, is_root=False)

Bases: object

Parameters:

• algorithm (str)

• code (str)

• obj (float)

• depth (int)

• parent (MCTSNode | None)

• visit (int)

• raw_info (Any | None)

• Q (float)

• is_root (bool)

add_child(child_node)

Parameters:

child_node (MCTSNode)

Return type:

None

llamda.ga.mcts.mcts_ahd module

class llamda.ga.mcts.mcts_ahd.AHDConfig(pop_size: int = 10, init_size: int = 4, fe_max: int = 1000, operators: list[str] = <factory>, m: int = 5, operator_weights: list[int] = <factory>)

Bases: object

Parameters:

• pop_size (int)

• init_size (int)

• fe_max (int)

• operators (list[str])

• m (int)

• operator_weights (list[int])

fe_max: int = 1000

init_size: int = 4

m: int = 5

operator_weights: list[int]

operators: list[str]

pop_size: int = 10

class llamda.ga.mcts.mcts_ahd.MCTS_AHD(config, problem, evaluator, llm_client, output_dir)

Bases: GeneticAlgorithm[AHDConfig, EohProblem]

Parameters:

• config (AHDConfig)

• problem (EohProblem)

• evaluator (Evaluator)

• llm_client (BaseClient)

• output_dir (str)

add2pop(population, offspring)

Parameters:

• population (list[MCTSIndividual])

• offspring (MCTSIndividual)

Return type:

None

expand(mcts, cur_node, nodes_set, option, name)

Parameters:

• mcts (MCTS)

• cur_node (MCTSNode)

• nodes_set (list[MCTSIndividual])

• option (str)

• name (str)

Return type:

list[MCTSIndividual]

run()

Return type:

tuple[str, str]

llamda.ga.mcts.mcts_ahd.manage_population(pop_input, size)

Parameters:

• pop_input (list[MCTSIndividual])

• size (int)

Return type:

list[MCTSIndividual]

llamda.ga.mcts.mcts_ahd.manage_population_s1(pop_input, size)

Parameters:

• pop_input (list[MCTSIndividual])

• size (int)

Return type:

list[MCTSIndividual]

Module contents