InnovationManager.java

package net.bmahe.genetics4j.neat;

import java.util.concurrent.ConcurrentHashMap;

import java.util.concurrent.atomic.AtomicInteger;

import org.apache.commons.lang3.Validate;

import org.apache.logging.log4j.LogManager;

import org.apache.logging.log4j.Logger;

/**

 * Manages innovation numbers for the NEAT (NeuroEvolution of Augmenting Topologies) algorithm.

 * 

 * <p>The InnovationManager is a critical component of the NEAT algorithm that tracks structural innovations in neural

 * networks through unique innovation numbers. This system enables NEAT to perform meaningful genetic crossover between

 * neural networks with different topologies while preserving historical information about when specific connections

 * were first added to the population.

 * 

 * <p>Key responsibilities:

 * <ul>

 * <li><strong>Innovation tracking</strong>: Assigns unique numbers to each new connection type (from-to node pair)</li>

 * <li><strong>Historical marking</strong>: Maintains consistent innovation numbers across the population</li>

 * <li><strong>Crossover support</strong>: Enables alignment of neural network structures during recombination</li>

 * <li><strong>Cache management</strong>: Provides efficient lookup and generation of innovation numbers</li>

 * </ul>

 * 

 * <p>NEAT innovation number system:

 * <ul>

 * <li><strong>Unique identification</strong>: Each unique connection (from-node → to-node) gets one innovation

 * number</li>

 * <li><strong>Population consistency</strong>: Same connection type across individuals gets same innovation number</li>

 * <li><strong>Temporal ordering</strong>: Innovation numbers reflect the historical order of structural mutations</li>

 * <li><strong>Crossover alignment</strong>: Enables gene alignment during genetic recombination</li>

 * </ul>

 * 

 * <p>Innovation number workflow:

 * <ol>

 * <li><strong>Mutation occurs</strong>: Add-connection mutation creates new connection type</li>

 * <li><strong>Innovation check</strong>: Manager checks if this connection type was seen before</li>

 * <li><strong>Number assignment</strong>: New types get new innovation numbers, existing types reuse numbers</li>

 * <li><strong>Population tracking</strong>: All individuals with same connection type share same innovation number</li>

 * <li><strong>Crossover alignment</strong>: Innovation numbers enable proper gene alignment during recombination</li>

 * </ol>

 * 

 * <p>Common usage patterns:

 * 

 * <pre>{@code

 * // Create innovation manager for new evolution run

 * InnovationManager innovationManager = new InnovationManager();

 * 

 * // During add-connection mutation

 * int fromNode = 0, toNode = 3;

 * int innovationNumber = innovationManager.computeNewId(fromNode, toNode);

 * Connection newConnection = Connection.of(fromNode, toNode, weight, innovationNumber, true);

 * 

 * // Reset cache between generations if needed

 * innovationManager.resetCache();

 * 

 * // Start with specific innovation number

 * InnovationManager manager = new InnovationManager(1000);

 * }</pre>

 * 

 * <p>Cache management strategy:

 * <ul>

 * <li><strong>Per-generation caching</strong>: Cache innovation numbers within each generation</li>

 * <li><strong>Cross-generation persistence</strong>: Innovation numbers remain consistent across generations</li>

 * <li><strong>Memory management</strong>: Reset cache periodically to prevent memory growth</li>

 * <li><strong>Concurrent access</strong>: Thread-safe operations for parallel genetic operations</li>

 * </ul>

 * 

 * <p>Performance considerations:

 * <ul>

 * <li><strong>O(1) lookup</strong>: Fast innovation number retrieval through hash map caching</li>

 * <li><strong>Memory efficiency</strong>: Cache only unique connection types seen in current generation</li>

 * <li><strong>Thread safety</strong>: Concurrent operations supported for parallel evolution</li>

 * <li><strong>Cache lifecycle</strong>: Reset cache between evolution runs to prevent memory leaks</li>

 * </ul>

 * 

 * <p>Integration with NEAT algorithm:

 * <ul>

 * <li><strong>Structural mutations</strong>: Add-connection mutations use innovation manager</li>

 * <li><strong>Genetic crossover</strong>: Innovation numbers enable gene alignment</li>

 * <li><strong>Compatibility distance</strong>: Innovation numbers used to identify matching, excess, and disjoint

 * genes</li>

 * <li><strong>Population management</strong>: Shared innovation manager across entire population</li>

 * </ul>

 * 

 * @see Connection

 * @see ConnectionPair

 * @see NeatChromosome

 * @see net.bmahe.genetics4j.neat.mutation.AddConnectionPolicyHandler

 */

public class InnovationManager {

	public static final int DEFAULT_INITIAL_ID = 0;

	private final AtomicInteger currentId;

	/**

	 * Constructs an innovation manager with the specified initial innovation number.

	 * 

	 * @param initialValue the starting innovation number for new innovations

	 */

	/**

	 * Constructs an innovation manager with the default initial innovation number (0).

	 */

	public InnovationManager() {

	/**

	 * Computes or retrieves the innovation number for a connection between two nodes.

	 * 

	 * <p>If this connection type (from-node → to-node) has been seen before, returns the existing innovation number from

	 * the cache. Otherwise, generates a new innovation number and caches it for future use. This ensures that the same

	 * connection type across different individuals in the population receives the same innovation number.

	 * 

	 * @param from the source node index of the connection

	 * @param to   the target node index of the connection

	 * @return the innovation number for this connection type

	 * @throws IllegalArgumentException if from equals to (self-connections not allowed)

	 */

	public int computeNewId(final int from, final int to) {

	}

	/**

	 * Resets the innovation cache, clearing all cached connection-to-innovation-number mappings.

	 * 

	 * <p>This method should be called between evolution runs or generations to prevent memory growth and ensure that

	 * innovation number assignment starts fresh. Note that this does not reset the current innovation number counter, so

	 * new innovations will continue to receive unique numbers.

	 */

	public void resetCache() {

}

Mutations

1.1
Location : <init>
Killed by : none Substituted 0 with 1 → SURVIVED Covering tests