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Nonlinear Trends in Modern Artificial Intelligence: A New Perspective

  • Elena N. BenderskayaEmail author
Part of the Topics in Intelligent Engineering and Informatics book series (TIEI, volume 4)

Abstract

Artificial intelligent systems capable of learning, setting goals, solving problems, finding new solutions and unforeseen behavior scenarios without external assistance exist in a variety of odd models, each using different sets of assumptions and each having its own limitations. The author argues whether the modern artificial intelligent systems can be called truly intelligent so that to be able to realize the vast capabilities of the human brain. In order to generalize core issues of the main artificial intelligence domains such as fuzzy logics, probabilistic reasoning, bio-inspired techniques, neural networks apparatus, and neuroscience advances together with the new areas of chaos theory and nonlinear dynamics, a multidisciplinary analysis has been employed in the work. In the analysis, the evolution of a particular mathematical apparatus is being considered to justify the application of dynamic models with unstable dynamics used to solve intelligent problems of the next generation. The conclusion is soundly based on the idea that the future of artificial intelligence lies in the sphere of nonlinear dynamics and chaos that is absolutely critical to understanding and modeling cognition processes.

Keywords

Fuzzy Logic Chaotic System Nonlinear Trend Chaotic Neural Network Dynamic Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Faculty of Computer ScienceSt. Petersburg State Polytechnical UniversitySt. PetersburgRussia

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