Variation (Crossover/Mutation)

Variation (Crossover/Mutation)#

class MutationBase#

Subclassed by Brush::Var::DeleteMutation, Brush::Var::InsertMutation, Brush::Var::PointMutation, Brush::Var::SplitMutation, Brush::Var::SubtreeMutation, Brush::Var::ToggleWeightOffMutation, Brush::Var::ToggleWeightOnMutation

Public Types

using Iter = tree<Node>::pre_order_iterator#

Public Static Functions

template<Brush::ProgramType T>
static inline auto find_spots(Program<T> &program, Variation<T> &variator, const Parameters &params)#
template<Brush::ProgramType T>
static auto mutate(Program<T> &program, Iter spot, Variation<T> &variator, const Parameters &params)#
template<ProgramType T>
class Variation#

Class representing the variation operators in Brush.

The Variation class is responsible for performing individual-level variations and handling the variation of a population in Brush. It contains methods for crossing individuals, mutating individuals, and varying a population.

Public Functions

Variation() = default#

Default constructor.

inline Variation(Parameters &params, SearchSpace &ss, Dataset &d)#

Constructor that initializes the Variation object with parameters and search space.

Parameters:

  • params – The parameters for the variation operator.

  • ss – The search space for the variation operator.

inline ~Variation()#

Destructor.

inline void init()#

Initializes the Variation object with parameters and search space.

Parameters:

  • params – The parameters for the variation operator.

  • ss – The search space for the variation operator.

std::tuple<std::optional<Individual<T>>, VectorXf> cross(const Individual<T> &mom, const Individual<T> &dad)#

Performs croearch_spaceover operation on two individuals.

Stochastically swaps subtrees between root and other, returning a new program.

The spot where the cross will take place in the root parent is sampled based on attribute get_prob_change of each node in the tree. After selecting the cross spot, the program will iterate through the other parent searching for all compatible sub-trees to replace.

Due to the stochastic behavior, it may come to a case where there is no candidate to replace the spot node. In this case, the method returns std::nullopt (and has overloads so it can be used in a boolean context).

If the cross succeeds, the child program can be accessed through the .value() attribute of the std::optional. TODO: update this documentation (it doesnt take the program but the individual. also update mutation documentation) This means that, if you use the cross as auto opt = mutate(parent, SS), either opt==false or opt.value() contains the child.

Parameters:

  • mom – The first parent individual.

  • dad – The second parent individual.

  • root – the root parent

  • other – the donating parent

Returns:

An optional containing the offspring individual if the crossover is successful, or an empty optional otherwise.

Template Parameters:

T – the program type

Returns:

std::optional that may contain the child program of type T

std::tuple<std::optional<Individual<T>>, VectorXf> mutate(const Individual<T> &parent, string choice = "")#

Performs mutation operation on an individual.

Stochastically mutate a program.

Types of mutation:

  • point mutation changes a single node.

  • insertion mutation inserts a node as the parent of an existing node, and fills in the other arguments.

  • deletion mutation deletes a node.

  • subtree mutation inserts a new subtree into the program.

  • toggle_weight_on mutation turns a node’s weight ON.

  • toggle_weight_off mutation turns a node’s weight OFF.

Every mutation has a probability (weight) based on global parameters. The spot where the mutation will take place is sampled based on attribute get_prob_change of each node in the tree. Inside each type of mutation, when a new node is inserted, it is sampled based on terminal_weights.

Due to the stochastic behavior, and the several sampling steps, it may come to a case where the search space does not hold any possible modification to do in the program. In this case, the method returns std::nullopt (and has overloads so it can be used in a boolean context).

If the mutation succeeds, the mutated program can be accessed through the .value() attribute of the std::optional.

This means that, if you use the mutation as auto opt = mutate(parent, SS), either opt==false or opt.value() contains the child program.

Parameters:

  • parent – The parent individual.

  • parent – the program to be mutated

  • SS – a search space

Returns:

An optional containing the mutated individual if the mutation is successful, or an empty optional otherwise.

Template Parameters:

T – program type

Returns:

std::optional that may contain the child program of type T

void vary(Population<T> &pop, int island, const vector<size_t> &parents)#

Handles variation of a population.

Parameters:

  • pop – The population to be varied.

  • island – The island index.

  • parents – The indices of the parent individuals.

  • p – The parameters for the variation operator.

void update_ss()#

Updates the probability distribution sampling for variation and nodes based on the given rewards.

Parameters:

  • pop – The population to update the selection strategy for.

  • rewards – The rewards obtained from the evaluation of individuals.

inline void vary_and_update(Population<T> &pop, int island, const vector<size_t> &parents, const Dataset &data, Evaluation<T> &evaluator)#

Varies a population and updates the selection strategy based on rewards.

This function performs variation on a population, calculates rewards, and updates the selection strategy based on the obtained rewards.

Parameters:

  • pop – The population to be varied and updated.

  • island – The island index.

  • parents – The indices of the parent individuals.

inline std::optional<Node> bandit_sample_terminal(DataType R, VectorXf &context)#
inline std::optional<Node> bandit_get_node_like(Node node, VectorXf &context)#
inline std::optional<Node> bandit_sample_op_with_arg(DataType ret, DataType arg, VectorXf &context, int max_args = 0)#
inline std::optional<Node> bandit_sample_op(DataType ret, VectorXf &context)#
inline VectorXf get_context(const Program<T> &program, Iter spot)#

Public Members

SearchSpace search_space#
Dataset &data#
Parameters parameters#
Contents