Естественные морфологические вычисления как основа способности к обучению у людей, других живых существ и интеллектуальных машин

Современная натурфилософия динамично развивается как сфера науки и является основой для комплексного подхода к рассмотрению естественных, искусственных практик и социально-гуманитарного знания. Как теоретические, так и практические знания приобретаются, систематизируются, накапливаются в активном и пассивном виде в процессе обучения. В данной статье рассматривается взаимосвязь между современными достижениями в понимании процесса обучения в различных научных сферах: прикладных науках об искусственном интеллекте (глубокое обучение, робототехника), естественных науках (нейробиология, когнитивистика, биология) и философии (вычислительная философия, философия сознания, натурфилософия). Рассматривается вопрос о том, что именно может помочь текущему развитию машинного обучения и искусственного интеллекта на данном этапе, вдохновленному естественными процессами, в частности: вычислительными моделями, например информационно-вычислительными методами морфологических вычислений. Помимо этого рассматривается, в какой степени модели и эксперименты в области машинного обучения и робототехники могут стимулировать исследования в области вычислительной когнитивной науки, нейробиологии и природных вычислений. Мы предполагаем, что понимание механизмов формирования способности к обучению может стать важным шагом в развитии глубокого обучения в контексте вычисления/обработки информации в рамках подхода, объединяющего коннекционизм и символьный подход. Так как все естественные интеллектуальные системы являются когнитивными, мы приводим аргументы в пользу эволюционного подхода к изучению познавательных процессов. Из этого следует, что достижение человеческого уровня интеллекта для иных систем возможно только через эволюцию и развитие. Таким образом, данная статья представляет собой вклад в теорию познания в рамках современной философии природы.

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