Page 156 - 49A Field Guide to Genetic Programming
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142                                                  14 Conclusions


               Today, decades later, we can see that indeed Turing was right. GP has
            started fulfilling his dream by providing us with a systematic method, based
            on Darwinian evolution, for getting computers to automatically solve hard
            real-life problems. To do so, it simply requires a high-level statement of
            what needs to be done and enough computing power.
               Turing also understood the need to evaluate objectively the behaviour ex-
            hibited by machines, to avoid human biases when assessing their intelligence.
            This led him to propose an imitation game, now known as the Turing test for
            machine intelligence, whose goals are wonderfully summarised by Samuel’s
            position statement quoted in the introduction of this book (page 1). The
            eight criteria for human competitiveness we discussed in Section 12.3 are
            essentially motivated by the same goals.
               At present GP is unable to produce computer programs that would pass
            the full Turing test for machine intelligence, and it might not be ready
            for this immense task for centuries. Nonetheless, thanks to the constant
            improvements in GP technology, in its theoretical foundations and in com-
            puting power, GP has been able to solve dozens of difficult problems with
            human-competitive results and to provide valuable solutions to many other
            problems (see Chapter 12). These are a small step towards fulfilling Turing
            and Samuel’s dreams, but they are also early signs of things to come. It is
            reasonable to predict that in a few years time GP will be able to routinely
            and competently solve important problems for us, in a variety of application
            domains with human-competitive performance. Genetic programming will
            then become an essential collaborator for many human activities. This will
            be a remarkable step forward towards achieving true human-competitive
            machine intelligence.
               This field guide is an attempt to chart the terrain of techniques and
            applications we have encountered in our journey in the world of genetic
            programming. Much is still unmapped and undiscovered. We hope this
            book will make it easier for other travellers to start many long and profitable
            journeys in this exciting world.














               If you have found this book to be useful, please feel free to redistribute it
            (see page ii). Should you want to cite this book, please refer to the entry for
            (Poli et al., 2008) in the bibliography.
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