[AISWorld] Final Call for Papers - AMCIS 2019 SIGODIS Mini-track "Artificial Intelligence and Intelligent Systems"

[Vijayan Sugumaran]

AMCIS 2019 - New Frontiers in Digital Convergence
Cancún, México, August, 15-17

Track: Semantics, Ontologies, Intelligence and Intelligent Systems (Sponsored by SIGODIS)

Mini-track : Artificial Intelligence and Intelligent Systems

Mini-track Chairs: Vijayan Sugumaran, sugumara at oakland.edu; Stefan Kim, stefan.kirn at uni-hohenheim.de 

Artificial Intelligence and Intelligent Systems are experiencing a resurgence and have been recognized as one of the most important developments in Information Systems. Significant progress has been made over the last few years in the development of computational intelligence techniques such as bio/nature-inspired computing, deep learning, and cognitive computing within the artificial intelligence domain. Similarly, there is an upsurge in the application of AI technologies and multi-agent systems in a variety of fields such as electronic commerce, supply chain management, resource allocation, intelligent manufacturing, mass customization, information retrieval and filtering, decision support, and healthcare. While research on various aspects of intelligent systems and semantic technologies is progressing at a very fast pace, this is only the beginning. There are still a number of issues that have to be explored in terms of the design, implementation and deployment of intelligent applications and multi-agent systems. For example, development of novel techniques for computational intelligence in support of deep learning, formal approaches for designing intelligent systems and agent based applications, ontology based information systems, and organizational impact of intelligent systems & semantic technologies are some of the areas in need of further research.

Best papers from this mini-track will be fast tracked for publication in a special issue of International Journal of Intelligent Information Technologies (http://www.idea-group.com/IJIIT).

Potential topics include but are not limited to:

• Neural Networks, Fuzzy Logic and Machine Learning Applications
• Bio and Nature Inspired Computing
• Evolutionary Computation
• Hybrid Learning, and Deep Learning applications
• Computational intelligence systems in healthcare, energy management, smart grids, mobile networks, internet of things, sensor networks, cloud computing, transportation systems, etc.
• Computational intelligence, analytical modeling, and simulation for big data analytics
• Computational Methods in Context Aware Web Systems
• Computational intelligence applications for Business Intelligence and decision making
• Application of intelligent agent and multi-agent systems in different domains
• Distributed Intelligent Systems
• Agents and web data mining
• Multi-agent technology and grid computing
• Architectures, environments and languages for e-commerce agents
• Automated shopping and trading agents
• Agent-based auction, negotiation and decision making
• Agent driven interoperability and distributed decision support
• Software agents and knowledge management
• Agent-based Business Analytics
• Business Intelligence and multi-agent systems

***Submission:***
Instructions on how to submit a manuscript can be found here https://amcis2019.aisconferences.org/submissions/call-for-papers/ 
The submission deadline is March 1st, 2019.

***Important dates:***
   - March 1, 2019: AMCIS manuscript submissions (completed research and Emergent Research Forum (ERF)) closes for authors at 10:00am PST
   - March 7, 2019: All papers have assigned reviewers
   - April 17, 2019: Authors notified of decision

=============================================
Vijayan Sugumaran, Ph.D.
Professor of Management Information Systems
Chair, Department of Decision and Information Sciences
Co-Director, Center for Data Science and Big Data Analytics
School of Business Administration
Oakland University
Rochester, MI 48309
Phone: 248-370-4649
Fax: 248-370-4275
Email: sugumara at oakland.edu
=============================================