NEAT is an advanced genetic algorithm technique that evolves both the weights and topologies of neural networks, enabling them to adapt and optimize over generations. It introduces innovation in evolutionary processes by maintaining a diverse set of solutions and allowing for gradual complexity increase through the structuring of genomes, making it a powerful approach for evolving neural networks and addressing the challenges in simulation environments.
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