In real world a great majority of processes are time-dependant by nature. Therefore, methodologies of processing data and information in dynamic environments are widely studied. In particular, application areas like for instance in business, medicine, or smart cities are expanding rapidly such that the trend creates the challenge for research community to build newinfrastructure aimed at meeting the innovative requirements.

One of the fundamental goals in computational intelligence is to achieve the ability to effective computer-assisted learning from noisy, uncertain and incomplete data in order to adapt to constantly changing environments. Examples of such dynamic environments, which require some well-defined and verified methods and tools, include Internet of Things networks and realtime systems. Substantial changes, concept drift and some newly emerging trends in dynamic environments can have an impact on the increasing number of imprecise predictive methods, the rate of false alarms and consequently it may influence the systems performance and/or security.

The special session aims at presenting novel approaches to learning and adaptation to dynamic environments both from theoretical and practical application-oriented perspective. 
This Special Session is intended to provide a forum for researchers in this area to exchange new ideas. So that we encourage the research community to submit their work in progress, concept papers, position papers, case studies, reports, review papers to present innovative ideas that can provoke a discussion and provide a feedback to the session participants, initiate collaborations and stimulate some creative thinking about promising research trends.