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Combining Evolutionary Algorithms and Neural Networks

Originally, EANNs were designed to replace learning with evolution, not to integrate the two mechanisms. Basically, many situations call for ANNs with memory, which requires recurrent links. Unfortunately, recurrent topologies make classic supervised learning via backpropagation very difficult. Disregarding recurrence, supervised learning is still inappropriate for most robotic applications, since omniscent teachers cannot provide the correct answer/response for each situation, particularly when a typical robot samples the environment (via it sensors) and reacts several times per second.