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Syntropic Counterpoints: Philosophical Content Generated Between Two Artificial Intelligence Clones

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Intelligent Technologies for Interactive Entertainment (INTETAIN 2018)

Abstract

In the project Syntropic Counterpoints, we are using discussions between Artificial Intelligence clones to generate creative content. Nevertheless, our focus is less on content analysis and more on the beauty of creation itself and given context by the machines. We are using a different recurrent neural network (RNN), and collective creativity approaches to support interactions between Artificial Intelligence clones and trigger a humanless creative process which should lead to unsupervised robot creativity. The robots are trained by using the publications of some of the greatest thinkers of their time such as Aristotle, Nietzsche, Machiavelli, Sun Tzu and confronted to the crucial questions related to humankind such as understanding of moral, aesthetic, ethic, strategy, politics, etc. Throughout this robot-robot interaction model, we are trying to investigate the possibilities and consider limitations of using artificial intelligence in context-based creative processes as well as to raise questions related to potential future phenomena of machines mindfulness.

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References

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Acknowledgement

We thank Marko Jovanovic, brilliant Software Engineer, who gave us technical solution and developed the Artificial Intelligence Clones we are using in the project.

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Correspondence to Predrag K. Nikolić .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Nikolić, P.K., Yang, H. (2019). Syntropic Counterpoints: Philosophical Content Generated Between Two Artificial Intelligence Clones. In: Cortez, P., Magalhães, L., Branco, P., Portela, C., Adão, T. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 273. Springer, Cham. https://doi.org/10.1007/978-3-030-16447-8_1

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  • DOI: https://doi.org/10.1007/978-3-030-16447-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16446-1

  • Online ISBN: 978-3-030-16447-8

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