Recently, we have a paper entitled “Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement Learning” accepted by the IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI).

The IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI) publishes original articles on emerging aspects of computational intelligence, including theory, applications, and surveys.

TETCI is an electronics only publication. TETCI publishes six issues per year.

Authors are encouraged to submit manuscripts in any emerging topic in computational intelligence, especially nature-inspired computing topics not covered by other IEEE Computational Intelligence Society journals. A few such illustrative examples are glial cell networks, computational neuroscience, Brain Computer Interface, ambient intelligence, non-fuzzy computing with words, artificial life, cultural learning, artificial endocrine networks, social reasoning, artificial hormone networks, computational intelligence for the IoT and Smart-X technologies.

Dr. Ran Cheng is an Associate Editor of the journal.