Automatic Generation of Scientific Theories

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Creativity is at the heart of scientific research, both in the natural and the social sciences. It is also at the basis of innovation in business and industry. Psychological research suggests that the Darwinian mechanisms of variation and selection are the key constituents of creativity. Similarly, philosophers of science such as Popper have noted the evolutionary character of scientific knowledge. However, with the exception of preliminary work by the PI, there has been no attempt to use computers to evolve scientific theories using mechanisms based on natural evolution. The aim of this research is to fill in this gap by proposing a novel way to generate theories. Theories will be automatically generated by computer programs using algorithms based on natural evolution. The success of the theories will be estimated by the extent to which they account for the experimental data, and the best theories will be selected for the next generation, possibly modified by mutation or crossover. The method will be applied to experiments in cognitive psychology, health psychology and behavioural economics. Currently, the development of scientific theories is considered the exclusive province of humans. This project will genuinely be transformative as it will challenge this conception and change the way theories are viewed in the social sciences: from static abstract objects to concrete objects that can be manipulated by computer programs. The proposed method will lead to more efficient ways to exploit empirical data for the development of theoretical knowledge, with implications for applied research in the long term.