AddNodePolicyHandler.java

package net.bmahe.genetics4j.neat.mutation;

import java.util.random.RandomGenerator;

import org.apache.commons.lang3.Validate;

import net.bmahe.genetics4j.core.chromosomes.Chromosome;

import net.bmahe.genetics4j.core.mutation.GenericMutatorImpl;

import net.bmahe.genetics4j.core.mutation.MutationPolicyHandler;

import net.bmahe.genetics4j.core.mutation.MutationPolicyHandlerResolver;

import net.bmahe.genetics4j.core.mutation.Mutator;

import net.bmahe.genetics4j.core.mutation.chromosome.ChromosomeMutationHandler;

import net.bmahe.genetics4j.core.spec.AbstractEAConfiguration;

import net.bmahe.genetics4j.core.spec.AbstractEAExecutionContext;

import net.bmahe.genetics4j.core.spec.mutation.MutationPolicy;

import net.bmahe.genetics4j.core.util.ChromosomeResolverUtils;

import net.bmahe.genetics4j.neat.spec.mutation.AddNode;

/**

 * Mutation policy handler for NEAT (NeuroEvolution of Augmenting Topologies) add-node mutations.

 * 

 * <p>AddNodePolicyHandler manages the structural mutation that adds new hidden nodes to NEAT neural networks by

 * splitting existing connections. This is one of the most important structural mutations in NEAT as it enables the

 * evolution of increasingly complex network topologies.

 * 

 * <p>Add-node mutation process:

 * <ol>

 * <li><strong>Connection selection</strong>: Choose an existing enabled connection to split</li>

 * <li><strong>Connection disabling</strong>: Disable the original connection</li>

 * <li><strong>Node creation</strong>: Create a new hidden node between the connection endpoints</li>

 * <li><strong>Connection replacement</strong>: Create two new connections through the new node</li>

 * <li><strong>Innovation tracking</strong>: Assign innovation numbers to new connections</li>

 * <li><strong>Weight preservation</strong>: Set weights to preserve network function</li>

 * </ol>

 * 

 * <p>Key characteristics:

 * <ul>

 * <li><strong>Topology complexity</strong>: Increases network depth and node count</li>

 * <li><strong>Function preservation</strong>: Maintains network behavior through careful weight setting</li>

 * <li><strong>Innovation tracking</strong>: New connections receive unique innovation numbers</li>

 * <li><strong>Gradual growth</strong>: Incrementally increases network complexity</li>

 * </ul>

 * 

 * <p>Network transformation:

 * <ul>

 * <li><strong>Before</strong>: Direct connection A → B with weight W</li>

 * <li><strong>After</strong>: Path A → NewNode → B with weights W₁ and W₂</li>

 * <li><strong>Weight strategy</strong>: Often W₁ = 1.0, W₂ = W to preserve function</li>

 * <li><strong>Node placement</strong>: New node gets next available index</li>

 * </ul>

 * 

 * <p>Common usage patterns:

 * 

 * <pre>{@code

 * // Create add-node mutation policy

 * AddNode addNodePolicy = AddNode.of(0.05); // 5% mutation rate

 * 

 * // Create policy handler

 * RandomGenerator randomGen = RandomGenerator.getDefault();

 * AddNodePolicyHandler<Double> handler = new AddNodePolicyHandler<>(randomGen);

 * 

 * // Check if handler can process the policy

 * boolean canHandle = handler.canHandle(resolver, addNodePolicy);

 * 

 * // Create mutator for the policy

 * Mutator mutator = handler.createMutator(executionContext, configuration, resolver, addNodePolicy);

 * 

 * // Apply mutation to population

 * List<Individual<Double>> mutatedPopulation = mutator.mutate(configuration, population);

 * }</pre>

 * 

 * <p>Integration with NEAT algorithm:

 * <ul>

 * <li><strong>Innovation management</strong>: Coordinates with InnovationManager for new connections</li>

 * <li><strong>Chromosome mutation</strong>: Delegates to NeatChromosomeAddNodeMutationHandler</li>

 * <li><strong>Population evolution</strong>: Applied based on configured mutation probability</li>

 * <li><strong>Complexity growth</strong>: Primary mechanism for increasing network complexity</li>

 * </ul>

 * 

 * <p>Structural impact:

 * <ul>

 * <li><strong>Hidden layer growth</strong>: Creates new hidden nodes that can form layers</li>

 * <li><strong>Computational depth</strong>: Increases potential computational complexity</li>

 * <li><strong>Feature detection</strong>: New nodes can detect intermediate features</li>

 * <li><strong>Representation power</strong>: Enhances network's representational capacity</li>

 * </ul>

 * 

 * <p>Performance considerations:

 * <ul>

 * <li><strong>Conservative application</strong>: Typically applied less frequently than weight mutations</li>

 * <li><strong>Innovation caching</strong>: Leverages InnovationManager for efficient tracking</li>

 * <li><strong>Memory efficiency</strong>: Minimal allocation during mutation operations</li>

 * <li><strong>Function preservation</strong>: Weight setting strategies maintain network behavior</li>

 * </ul>

 * 

 * @param <T> the fitness value type (typically Double)

 * @see AddNode

 * @see net.bmahe.genetics4j.neat.mutation.chromosome.NeatChromosomeAddNodeMutationHandler

 * @see MutationPolicyHandler

 * @see InnovationManager

 */

public class AddNodePolicyHandler<T extends Comparable<T>> implements MutationPolicyHandler<T> {

	private final RandomGenerator randomGenerator;

	/**

	 * Constructs a new add-node policy handler with the specified random generator.

	 * 

	 * <p>The random generator is used for stochastic decisions during mutation application, including selection of

	 * individuals to mutate and selection of connections to split.

	 * 

	 * @param _randomGenerator random number generator for stochastic mutation operations

	 * @throws IllegalArgumentException if randomGenerator is null

	 */

	/**

	 * Determines whether this handler can process the given mutation policy.

	 * 

	 * <p>This handler specifically processes AddNode mutation policies, which configure the parameters for adding new

	 * hidden nodes to NEAT neural networks.

	 * 

	 * @param mutationPolicyHandlerResolver resolver for nested mutation policies

	 * @param mutationPolicy                the mutation policy to check

	 * @return true if the policy is an AddNode instance, false otherwise

	 * @throws IllegalArgumentException if any parameter is null

	 */

	@Override

	public boolean canHandle(final MutationPolicyHandlerResolver<T> mutationPolicyHandlerResolver,

			final MutationPolicy mutationPolicy) {

	}

	/**

	 * Creates a concrete mutator for add-node mutations.

	 * 

	 * <p>This method resolves the appropriate chromosome mutation handlers for NEAT chromosomes and creates a generic

	 * mutator that applies add-node mutations according to the specified policy parameters.

	 * 

	 * <p>Mutator creation process:

	 * <ol>

	 * <li>Extract population mutation probability from the policy</li>

	 * <li>Resolve chromosome-specific mutation handlers</li>

	 * <li>Create generic mutator with resolved components</li>

	 * <li>Return configured mutator ready for population application</li>

	 * </ol>

	 * 

	 * @param eaExecutionContext            execution context containing NEAT-specific components

	 * @param eaConfiguration               evolutionary algorithm configuration

	 * @param mutationPolicyHandlerResolver resolver for chromosome mutation handlers

	 * @param mutationPolicy                the add-node mutation policy

	 * @return a configured mutator for applying add-node mutations

	 * @throws IllegalArgumentException if any parameter is null

	 */

	@Override

	public Mutator createMutator(final AbstractEAExecutionContext<T> eaExecutionContext,

			final AbstractEAConfiguration<T> eaConfiguration,

			final MutationPolicyHandlerResolver<T> mutationPolicyHandlerResolver, MutationPolicy mutationPolicy) {

				chromosomeMutationHandlers,

				mutationPolicy,

				populationMutationProbability);

	}

}

Mutations

1.1
Location : createMutator
Killed by : none removed call to net/bmahe/genetics4j/neat/spec/mutation/AddNode::populationMutationProbability → SURVIVED Covering tests