
How Evolution Generates Complexity, Diversity and Intelligence?
Let's Probe the Mysteries of Evolving Machine Intelligence

Latest News
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One paper accepted by IEEE TAI
2022-06-27
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One paper accepted by ICML 2022
2022-05-15
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One paper accepted by IEEE TCYB
2022-04-02
About EMI Group
The Evolving Machine Intelligence (EMI) group was founded in September 2018, affiliated with Southern University of Science and Technology (SUSTech), China. Generally, our research motivations can be interpreted at three levels:
- Philosophically, we are motivated to understand how evolution generates complexity, diversity and intelligence;
- Scientifically, we are motivated to study how intelligence can be made evolvable;
- Technically, we are motivated to design learning/optimization computing paradigm across areas between evolutionary computation and deep learning, reinforcement learning, operation research, etc.
Our cutting-eadge research outcomes mainly fall into the interdisciplinary fields of deep neuroevolution, evolutionary optimization, and evolutonary modeling, which provide end-to-end solutions to applications in edge computing, intelligent manufacturing, etc.

Deep Neuroevolution

Evolutonary Optimization

Evolutionary Modeling
