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AICS 2013 : International Conference on Artificial Intelligence and Computer Science 2013 | |||||||||||||||||
Link: http://worldconferences.net/aics2013/ | |||||||||||||||||
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Call For Papers | |||||||||||||||||
The AICS2013 Conference Committee cordially invites submission of papers to the International Conference on Artificial Intelligence and Computer Science. The purpose of the conference is to promote research and scientific interchange among researchers and practitioners in all areas of Artificial Intelligence. The conference is hosted by WorldConferences.net, Koperasi Kolej Universiti Islam Antarabangsa Selangor. The venue will be at the beautiful island of Langkawi, MALAYSIA.
***The AICS2013 Secretariat will only accept maximum of 30 papers for the presentation in the conference and publication in the e-journal. Conference date: 25 & 26 November 2013 Sub-themes 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 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 Search and meta-heuristics Swarm Optimization Integration of AI with other technologies Evaluation of AI tools Social intelligence (markets and computational societies) Social impact of AI Emerging technologies Applications (including: computer vision, signal processing, pattern recognition, face recognition, finger print recognition, education, emerging applications, …) Machine Learning - General Machine Learning Theory - Statistical learning theory - Unsupervised and Supervised Learning - Hierarchical learning models - Relational learning models - Meta learning - Stochastic optimization - Simulated annealing - Heuristic optimization techniques - Neural networks - Reinforcement learning - Multi-criteria reinforcement learning - Multiple hypothesis testing - Decision making - Markov chain Monte Carlo (MCMC) methods - Graphical models - Gaussian graphical models - Cross-Entropy method - Ant colony optimization - Time series prediction - Fuzzy logic and learning - Inductive learning and applications - Grammatical inference - General Graph-based Machine Learning Techniques - Graph-based semi-supervised learning - Graph clustering - Graph learning based on graph transformations and grammars - Graph learning based on graph matching - Information-theoretical approaches to graphs - Motif search - Network inference - General issues in graph and tree mining - Computational Intelligence - Induction of document grammars - Supervised and unsupervised classification of web data - General Structure-based approaches in information retrieval, web authoring, information extraction, and web content mining - Latent semantic analysis - Intelligent linguistic - Aspects of text technology - Computational vision - Computational Statistics |
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