(apologies for cross-posting)
Final Call for Papers
Foundations of Computational Intelligence (FOCI 2023)
The 2023 IEEE Symposium on Foundations of Computational Intelligence (FOCI 2023) will take place as part of the IEEE Symposium Series on Computational Intelligence (SSCI 2023), which is a flagship annual meeting organized by the IEEE Computational Intelligence Society. It serves as a primary forum for multidisciplinary research in computational intelligence. SSCI 2023 will be held in Mexico City from December 5th to 8th, 2023. The conference proceedings of the SSCI 2023 will be included in the IEEE Xplore and indexed by all major databases.
IEEE FOCI’23 provides an ideal forum for those who are interested in the foundational issues of computational intelligence to exchange their ideas and present their latest findings. Participants of FOCI’23 will also benefit from the interaction at one location with the participants of several other symposia running concurrently at IEEE SSCI 2023, each highlighting various aspects of computational intelligence. As a whole, this international event will attract top researchers, practitioners, and students from around the world to discuss the latest advances in the field of computational intelligence.
Topics
- Fuzzy Logic: Non-standard fuzzy sets; Granular computing; Computing with words; Aggregation/fusion; Fuzzy sets and statistics; Uncertainty; Decision-making; General theoretical issues; Generalisation in neural, fuzzy and evolutionary learning; Fuzzy logic and fuzzy set theory; Lattice theory and multi-valued logic; Approximate reasoning; Type-2 fuzzy logic; Rough sets and random sets; Fuzzy mathematics; Fuzzy measure and integral; Possibility theory and imprecise probability
- Neural Networks and other machine learning techniques: Neural computation; Self-organizing maps; Recurrent networks; Multilayer perceptrons; Deep Learning, convolutional neural networks, GANs.; Autoencoders; Evolutionary neural networks; Neural networks for pattern recognition; Neural netwoks for prediction and optimization; Neural networks for principal component analysis; General regression neural networks; Neural networks as/and fuzzy systems; Radial basis functions; Learning theory; Reinforcement learning; Generalization in neural networks
- Evolutionary Computation: Theoretical foundations of bio-inspired heuristics; Exact and approximation runtime analysis; Fixed budget computations; Black box complexity; Self-adaptation; Population dynamics; Fitness landscape and problem difficulty analysis; No Free Lunch Theorems; Statistical approaches for understanding the behaviour of bio-inspired heuristics; Computational studies of a foundational nature
- All bio-inspired search heuristics will be considered for all problem domains including: Combinatorial and continuous optimization; Single-objective and multi-objective optimization; Constraint handling; Dynamic and stochastic optimization; Co-evolution and evolutionary learning
Paper submission
Each paper should be between 4 and 6 pages, inclusive of figures, tables, and references. All papers must be submitted using the IEEE conference template, found at https://www.ieee.org/conferences/publishing/templates.html
To submit your paper, click on “Submit a contribution to SSCI 2023” in https://conf.papercept.net/conferences/scripts/start.pl
(requires registration) using the symposium code FOCI.
In addition, SSCI 2023 offers a “Presentation-Only” option, which requires a two-page abstract. Accepted submissions will be presented orally at the conference and listed in the final program, but will not be available in IEEE Xplore.
For more details, please follow the instructions at
https://attend.ieee.org/ssci-2023/paper-submission/
Important dates
Paper Submissions: July 31, 2023 (no further extensions!)
Paper Acceptance: August 31, 2023
Camera-ready Paper: September 20, 2023
Early Registration: September 20, 2023
Conference dates: December 5-8, 2023
Symposium Chairs
Domingo López-Rodríguez, University of Malaga, Spain
Leonardo Franco, University of Florida, USA
Chao Qian, Nanjing University, China