MULTI-DISCIPLINARY INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE

MIWAI 2019


Artificial Intelligence



The Multi-disciplinary International Conference on Artificial Intelligence (MIWAI), formerly called The Multi-disciplinary International Workshop on Artificial Intelligence, is a well established scientific venue in the field of artificial Intelligence. MIWAI was established more than 10 years. This conference aims to be a meeting place where excellence in AI research meets the needs for solving dynamic and complex problems in the real world. The academic researchers, developers, and industrial practitioners will have extensive opportunities to present their original work, technological advances and practical problems. Participants can learn from each other and exchange their experiences in order to fine tune their activities in order to help each other better. The main purposes of the MIWAI series of conferences are:
- To provide a meeting place for AI researchers and practitioners.
- To inform research students about cutting-edge AI research via the presence of outstanding international invited speakers.
- To raise the standards of practice of AI research by providing researchers and students with feedback from an internationally-renowned program committee.
Artificial intelligence is a broad area of research. We encourage researchers to submit papers in the following areas but not limited to:
THEORY, METHODS AND TOOLS
Cognitive Science
Computational Philosophy
Computational Intelligence
Computer Vision
Evolutionary Computing
Game Theory
Knowledge Representation and Reasoning
Machine Learning
Multi-agent Systems
Natural Language Processing
Planning and Scheduling
Robotics
Speech Recognition
Uncertainty in AI
Vision
Web and AI
APPLICATIONS
Ambient Intelligence
Big Data
Biometrics
Bioinformatics
Chatbots
Decision Support Systems
E-commerce
Industrial Applications of AI
Knowledge Management
Telecommunications and Web Services
Surveillance
Spam Filtering
Software Engineering
Social Networking
Security
Semantic Web
Recommender Systems
Privacy
SUBMISSION GUIDELINES
Both research and application papers are solicited. All submitted papers will be carefully peer-reviewed on the basis of technical quality, relevance, significance, and clarity.
Each paper should have no more than twelve (12) pages in the Springer-Verlag LNCS style. The authors' names and institutions should not appear in the paper. Unpublished work of the authors should not be cited. Springer-Verlag author instructions are available at: http://www.springer.com/lncs