Hitoshi Iba received his Ph.D. degree from The University of Tokyo, Japan, in 1990. From 1990 to 1998, he was with the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He has been with The University of Tokyo since 1998 and is currently a professor at the Graduate School of Information and Communication Engineering there. His research interests include evolutionary computation, genetic programming, bioinformatics, foundations of artificial intelligence, artificial life, complex systems, and robotics.

“The main aim of this work is to present and elaborate the bridge between theoretical approaches and the concrete, real-life challenges in genetics. … the author's efforts to present these concepts in an accessible manner brings the edge of research within the reach of a wider audience. The examples and the algebraic formalism throughout, augmented by the relevant references … open this field to undergraduates, postgraduates and established researchers alike and provide a solid starting point to more progressive research.” (Irina Ioana Mohorianu, zbMATH 1394.68003, 2018)

• Introduction.- Meta-heuristics, machine learning and deep learning methods.- Evolutionary approach to deep learning.- Machine learning approach to evolutionary computation.- Evolutionary approach to gene regulatory networks.- Conclusion.

Hitoshi Iba received his Ph.D. degree from The University of Tokyo, Japan, in 1990. From 1990 to 1998, he was with the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He has been with The University of Tokyo since 1998 and is currently a professor at the Graduate School of Information and Communication Engineering there. His research interests include evolutionary computation, genetic programming, bioinformatics, foundations of artificial intelligence, artificial life, complex systems, and robotics.

“The main aim of this work is to present and elaborate the bridge between theoretical approaches and the concrete, real-life challenges in genetics. … the author's efforts to present these concepts in an accessible manner brings the edge of research within the reach of a wider audience. The examples and the algebraic formalism throughout, augmented by the relevant references … open this field to undergraduates, postgraduates and established researchers alike and provide a solid starting point to more progressive research.” (Irina Ioana Mohorianu, zbMATH 1394.68003, 2018)

• Introduction.- Meta-heuristics, machine learning and deep learning methods.- Evolutionary approach to deep learning.- Machine learning approach to evolutionary computation.- Evolutionary approach to gene regulatory networks.- Conclusion.

Hitoshi Iba received his Ph.D. degree from The University of Tokyo, Japan, in 1990. From 1990 to 1998, he was with the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He has been with The University of Tokyo since 1998 and is currently a professor at the Graduate School of Information and Communication Engineering there. His research interests include evolutionary computation, genetic programming, bioinformatics, foundations of artificial intelligence, artificial life, complex systems, and robotics.

“The main aim of this work is to present and elaborate the bridge between theoretical approaches and the concrete, real-life challenges in genetics. … the author's efforts to present these concepts in an accessible manner brings the edge of research within the reach of a wider audience. The examples and the algebraic formalism throughout, augmented by the relevant references … open this field to undergraduates, postgraduates and established researchers alike and provide a solid starting point to more progressive research.” (Irina Ioana Mohorianu, zbMATH 1394.68003, 2018)

• Introduction.- Meta-heuristics, machine learning and deep learning methods.- Evolutionary approach to deep learning.- Machine learning approach to evolutionary computation.- Evolutionary approach to gene regulatory networks.- Conclusion.