The Evolution of Everything (EvE) and Genetic
Programming
W.P. Worzel
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.
Keywords Internet • Internet of Things • Fog Lifter • Combinators • SKGP
- P2P • AllJoyn • IOx • FRP • Blockchain • Functional relational program-
ming • Data flow design • Evolutionary reinforcement learning
1 Background
Currently data is collected from many devices across the Internet and uploaded to
data centers where the data is processed in the aggregate. The notion of the Internet
of Things (IoT) is characterized by an increasing number of devices at the edge of
the Internet gathering data for focused purposes. Many of these devices are sensors
or packages of sensors. Specialized industrial sensors connected to the Internet are
used for many purposes such as chemical production facilities, the power grid, and
agriculture. Homes and specialized personal devices such as personal fitness and
health devices, entertainment centers, and thermostats are also connected to the
W.P. Worzel ()
Fog Lifter Inc., 1314 Beechwood Dr., Ann Arbor, MI 48103, USA
e-mail:[email protected]
© Springer International Publishing Switzerland 2016
R. Riolo et al. (eds.),Genetic Programming Theory and Practice XIII,
Genetic and Evolutionary Computation, DOI 10.1007/978-3-319-34223-8_8
137