The last few decades have seen a new era of artificial intelligence (AI) focusing on the principles, theoretical aspects, and design methodology of algorithms gleaned from nature. Examples are artificial neural networks inspired by mammalian neural systems, evolutionary computation inspired by natural selection in biology, simulated annealing inspired by thermodynamics principles, and swarm intelligence inspired by the collective behavior of insects or microorganisms, and so on, interacting locally with their environment, therein causing coherent functional global patterns to emerge. These techniques have found their way into solving real world problems in science, business, technology, commerce, and also to a great extent in measuring systems.

Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains, in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. To name a few, we have microwave ovens, washing machines, and digital cameras that can figure out on their own what settings to use to perform their tasks optimally; they have a reasoning capability, make intelligent decisions, and learn from experience. As usual, defining computational intelligence is not an easy task. In a nutshell, which becomes quite apparent in light of the current research pursuits, the area is heterogeneous with a combination of such technologies as neural networks, fuzzy systems, evolutionary computation, swarm intelligence, and probabilistic reasoning. The recent trend is to integrate different components to take advantage of complementary features and to develop a synergistic system. Hybrid architectures like neuro-fuzzy systems, evolutionary-fuzzy systems, evolutionary-neural networks, evolutionary-neuro-fuzzy systems, and so on, are widely applied for real-world problem solving.

Computational Intelligence Group at Jinan University is a young research group, focusing on  various different hybrid intelligent computing approaches to solve the real world problems.

We are looking for extensive international collaborators and welcome scholars from the world to visit our Lab.


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