Symposium on Artificial Intelligence (CSCI-ISAI)

by admin last modified Jan 04, 2020 02:47 PM
All accepted papers of all symposiums will be published by Conference Publishing Services, CPS: as part of the proceedings of The 2019 International Conference on Computational Science and Computational Intelligence (CSCI'19).


Past conference proceedings can be accessed via IEEE Xplore Digital Library at:


Since its inception, CSCI proceedings have always been approved and included into IEEE Xplore indexation/digital-library citation index databases.

Scope & Topics

   Artificial Intelligence (AI) is the science and engineering of making
   intelligent machines and systems. This is an important multi-disciplinary
   field which is now an essential part of technology industry, providing
   the heavy lifting for many of the most challenging problems in
   computational science. Since Machine Learning has strong ties with AI,
   this symposium also covers the field of Machine Learning. The list of
   topics below is by no means meant to be exhaustive.
Artificial Intelligence:
   Brain models, Brain mapping, Cognitive science; Natural language
   processing; Fuzzy logic and soft computing; Software tools for AI; Expert
   systems; Decision support systems; Automated problem solving; Knowledge
   discovery; Knowledge representation; Knowledge acquisition; Knowledge-
   intensive problem solving techniques; Knowledge networks and management;
   Intelligent information systems; Intelligent data mining and farming;
   Intelligent web-based business; Intelligent agents; Intelligent networks;
   Intelligent databases; Intelligent user interface; AI and evolutionary
   algorithms; Intelligent tutoring systems; Reasoning strategies;
   Distributed AI algorithms and techniques; Distributed AI systems and
   architectures; Neural networks and applications; Heuristic searching
   methods; Languages and programming techniques for AI; Constraint-based
   reasoning and constraint programming; Intelligent information fusion;
   Learning and adaptive sensor fusion; Search and meta-heuristics; Multi-
   sensor data fusion using neural and fuzzy techniques; Integration of
   AI with other technologies; Evaluation of AI tools; Social intelligence
   (markets and computational societies); Social impact of AI; Emerging
   technologies; and Applications (including: computer vision, signal
   processing, military, surveillance, robotics, medicine, pattern
   recognition, face recognition, finger print recognition, finance and
   marketing, stock market, education, emerging applications, ...).
Machine Learning:
   Statistical learning theory; Unsupervised and Supervised Learning;
   Multivariate analysis; Hierarchical learning models; Relational
   learning models; Bayesian methods; Meta learning; Stochastic
   optimization; Simulated annealing; Heuristic optimization techniques;
   Neural networks; Reinforcement learning; Multi-criteria reinforcement
   learning; General Learning models; Multiple hypothesis testing;
   Decision making; Markov chain Monte Carlo (MCMC) methods; Non-
   parametric methods; Graphical models; Gaussian graphical models;
   Bayesian networks; Particle filter; Cross-Entropy method; Ant colony
   optimization; Time series prediction; Fuzzy logic and learning;
   Inductive learning and applications; Grammatical inference; Graph
   kernel and graph distance methods; Graph-based semi-supervised
   learning; Graph clustering; Graph learning based on graph
   transformations; Graph learning based on graph grammars; Graph
   learning based on graph matching; Information-theoretical approaches
   to graphs; Motif search; Network inference; Aspects of knowledge
   structures; Computational Intelligence; Knowledge acquisition and
   discovery techniques; Induction of document grammars; General
   Structure-based approaches in information retrieval, web authoring,
   information extraction, and web content mining; Latent semantic
   analysis; Aspects of natural language processing; Intelligent
   linguistic; Aspects of text technology; Biostatistics; High-
   throughput data analysis; Computational Neuroscience; and
   Computational Statistics.
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