虚拟生物圈中人工生物进化条件下的新生模型的科学基础、部分成果和展望

Mykhailo Zachepylo, Oleksandr Yushchenko
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摘要

这项研究旨在深入了解虚拟生物圈错综复杂的数字生态系统,目的是阐明和复制人工智能的出现和进化--即 "noogenesis"。我们对虚拟生物圈内的现有研究进行了全面分析,以便深入了解人工代理参与复杂互动的动态生态系统建模的复杂性。神经网络在这些环境中塑造人工生物适应性行为的关键作用得到了强调。对神经网络进化方法的细致研究表明,随着时间的推移,神经网络结构的复杂性也在不断演变,最终促进了灵活的智能行为。然而,在培育虚拟生物圈内基于进化的交流与合作能力方面,却缺乏研究。针对这一空白,我们引入了一个模型,并通过模拟实验加以证实。仿真结果生动地说明了该模型在培育适应性生物方面的卓越能力,这些生物具有对动态环境变化做出有效反应的能力。这些适应性实体显示出对能源消耗和资源获取的高效优化。此外,它们还表现出了智力和身体上的转变,这都归功于增强拓扑神经进化论所启发的进化和编码原理。值得注意的是,该模型内在的进化过程显然与环境本身有着千丝万缕的联系,从而与本研究的总体目标完美契合。研究人员概述了这一领域未来的研究方向。这些研究方向为进一步探索虚拟生物环境中人造生物的进化以及高级通信与合作能力的出现奠定了基础。这些进步有可能将人工生命和人工智能的理解和能力提升到新的水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
THE SCIENTIFIC BASIS, SOME RESULTS, AND PERSPECTIVES OF MODELING EVOLUTIONARILY CONDITIONED NOOGENESIS OF ARTIFICIAL CREATURES IN VIRTUAL BIOCENOSES
This research aimed to gain a profound understanding of virtual biocenoses intricate digital ecosystems, with the goal of elucidating and replicating the emergence and evolution of intelligence in artificial creatures – referred to as noogenesis. A comprehensive analysis of existing studies within virtual biocenoses was undertaken to glean valuable insights into the complexities of modeling dynamic ecosystems where artificial agents engaged in intricate interactions. The pivotal role of neural networks in shaping the adaptive behaviors of artificial creatures within these environments was underscored. A meticulous investigation into neural networks' evolution methodologies revealed the evolution of their architecture complexity over time, culminating in the facilitation of flexible and intelligent behaviors. However, a lack of study existed in the domain of nurturing evolutionary-based communication and cooperation capabilities within virtual biocenoses. In response to this gap, a model was introduced and substantiated through simulation experiments. The simulation results vividly illustrated the model's remarkable capacity to engender adaptive creatures endowed with the capability to efficiently respond to dynamic environmental changes. These adaptive entities displayed efficient optimization of energy consumption and resource acquisition. Moreover, they manifested both intellectual and physical transformations attributed to the evolution and encoding principles inspired by the NeuroEvolution of Augmented Topologies. Significantly, it became apparent that the evolutionary processes intrinsic to the model were inextricably linked to the environment itself, thus harmonizing seamlessly with the overarching goal of this research. Future research directions in this field were outlined. These pathways provided a foundation for further exploration into the evolution of artificial creatures in virtual biocenoses and the emergence of advanced communication and cooperation capabilities. These advancements hold the potential to move artificial life and artificial intelligence to new levels of understanding and capability.
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