Abstract
The Internet is entering a new period of growth driven by an increasing number of processors connected at the edge of the Internet. Many of these processors are sensors that continuously collect data. By 2020, it is projected that there may be more than 20 billion (1000 million) devices connected to the Internet. Collectively these devices are called the Internet of Things (IoT) or the Internet of Everything (IoE). The sheer volume of the data that will be gathered creates new problems for an economy that is increasingly driven by data analytics. It is likely that the devices at the edge of the Internet will take part in the processing of data for analytics by using distributed computing among edge devices. Genetic Programming could play a unique role in this environment because of its ability not only to gather and analyze data, but to control the evolution and use of other machine learning algorithms. The confluence of unimaginable streams of real-world data and emergent behaviors may give rise to the question of whether the evolution of intelligence in the natural world can be recreated using evolutionary tools.
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Worzel, W.P. (2016). The Evolution of Everything (EvE) and Genetic Programming. In: Riolo, R., Worzel, W., Kotanchek, M., Kordon, A. (eds) Genetic Programming Theory and Practice XIII. Genetic and Evolutionary Computation. Springer, Cham. https://doi.org/10.1007/978-3-319-34223-8_8
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