Creativity research

The research focuses on how the “new” emerges in social and technological systems and how humans and machines explore the space of possibilities and find new solutions.

The "Creativity, Innovation and Artificial Intelligence" team is the newest team of the lab. It started its activities at the end of 2017 and it focuses on the investigation of the processes behind innovation and human creativity and their interplay with the most recent advances in Artificial Intelligence, Machine Learning and Inference methods. From this perspective, the team is playing the role of a gluing interface for all the other activities of the lab. This is inline with a general trend: that of breaching the walls between teams and creating opportunities for fruitful exchanges and cross-fertilization. In the very spirit of creativity, this will help in seeding new ideas and let them blossom in a fertile breeding ground.

Towards a science of the new

Historically the notion of ‘the new’ has always posed challenges to humankind. What is new often defies the natural tendency of humans to predict and control future events. Despite very original mathematical constructions proposed so far, we think a coherent theoretical framework to grasp the notion of space of the possible is still lacking. Given this context, the research aims at providing a coherent and self-consistent mathematical formulation of the space of the possibilities - which includes its structure and its restructuring while it gets explored - and a mathematical modelling of the way systems - biological, technological, social - explore it at the individual and collective levels. Mathematically, the team faces extremely challenging problems connected to the following facts:

  1. we do not know the topology of the space of possibilities, nor how to extract it from the data;
  2. we do not know how this structure evolves over time at the individual and collective level;
  3. we still need a coherent and self-consistent mathematical formulation that, beyond explaining stylised facts (statistical laws, correlation and triggering effects, etc.), is able to cast concrete predictions to be grounded on actual data. Specific goals can be summarised as follows:
    1. establish an operational definition of space of possibilities and devise methods and tools to chart it;
    2. develop a self-consistent theory of the emergence of the new as guided by the different active principles;
    3. identify the best thriving environments for creativity and innovation with concrete applications in areas like education, research and business.

The application side of this research also includes the development of new recommendation strategies for the exploration of the space of possibilities (e.g., which products areas will likely to drive the market), the evaluation of new avenues and the quantification of innovative behaviours and the prediction of future success of novel elements.

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Publications

Sakellariou, J., Tria, F., Loreto, V. and Pachet, F. Maximum entropy models capture melodic styles. Scientific Reports, 7(9172), August 2017
2017
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Sakellariou, J., Tria, F., Loreto, V. and Pachet, F. Maximum entropy models capture melodic styles. arXiv:1610.03414, October 2016 https://arxiv.org/abs/1610.03414
2016
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Cuskley, C., Colaiori, F., Castellano, C., Loreto, V., Pugliese, M. and Tria, F. The adoption of linguistic rules in native and non-native speakers: Evidence from a Wug task. Journal of Memory and Language, 84:205-223, 2015
2015
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Francesca, T., Vito D.P., S., Salikoko S., M. and Loreto, V. Modeling the Emergence of Contact Languages. PLoS ONE, 10(4):e0120771, 2015
2015
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Monechi, B., Vito D. P., S. and Loreto, V. Congestion Transition in Air Traffic Networks. PLoS ONE, 10(5):e0125546, 05 2015
2015
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2015
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Rodi, G. C., Loreto, V., Servedio, D. P. and Tria, F. Optimal Learning Paths in Information Networks. Sci. Rep., 5, 06 2015
2015
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Sakellariou, J., Tria, F., Loreto, V. and Pachet, F. Maximum Entropy Model for Melodic Patterns. ICML Workshop on Constructive Machine Learning, Paris (France), July 2015
2015
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