The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components. It is generally believed that complex problems can be easier solved with such integrated or hybrid methods. Some of the existing efforts combine what are called soft computing methods (fuzzy logic, neural networks and evolutionary algorithms) either among themselves or with more traditional AI technologies such as logic and rules. Another stream of efforts integrates case-based reasoning and machine learning with soft computing and traditional AI methods. Yet another integrates agent-based approaches with logic and non-symbolic approaches. Some of the combinations have been quite important and have been more extensively used, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. However, there are other combinations that are still under investigation, such as those related to semantic web and deep learning as well as to swarm intelligence algorithms. In some cases, combinations are based on first principles, but in most cases, they are created in the context of specific applications.

The Workshop is intended to become annual forum for exchanging experience and ideas among researchers who are dealing with combining intelligent methods either based on first principles or in the context of specific applications. Topics of interest include (but not limited to) the following:


Topics of interest include (but are not limited to) the following:

-Bayesian Networks
-Case-Based Reasoning
-Deep Learning
-Ensemble learning, Ensemble methods
-Evolutionary Algorithms
-Evolutionary Neural Systems
-Fuzzy-Evolutionary Systems
-Hybrid Approaches for the Web
-Hybrid Knowledge Representation Approaches & Systems
-Hybrid and Distributed Ontologies
-Information Fusion Techniques
-Integrations of Neural Networks
-Intelligent Agents Integrations
-Integrations of Statistical and Symbolic AI Approaches
-Intelligent Agents Integrations
-Machine Learning Combinations
-Neuro-Fuzzy Approaches/Systems
-Reinforcement learning
-Semantic Web Technologies Integrations
-Swarm intelligence methods & integrations
-Applications
~Agents & Multi-agent Systems
~Big Data
~Biology, Computational Biology & Bioinformatics
~Decision Support and Recommender systems
~Economics, Business and Forecasting Applications
~Education & Distance Learning
~Industrial & Engineering applications
~Medicine & Health Care
~Multimodal Human Computer Interaction
~Natural language Processing and Understanding
~Planning, Scheduling, Search & Optimization
~Robotics
~Social Networks