CIL is an interdisciplinary research project by several universities. We are looking for a (detailed) logo for our research project "Collaborative Interactive Learning" (CIL):
The logo should embody the project idea and represent the relationships and information flows between the interacting entities (internet, smart systems, humans) that create knowledge.
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Imagine that in the centre is a smart (learning) system, that becomes more intelligent while it refines its algorithms autonomously. It asks other information and knowledge resources (e.g. humans, internet, other smart systems) e.g. to response to questions or to solve tasks to verify and/ or create new knowledge. Against that background different types of collaboration (e.g. human-human, human-smart system/machine and among smart systems) will take place.
The advantages of such smart (learning) systems are e.g. that complex problems can be solved that an indivdual entity cannot solve; humans benefit from the collective intelligence of such systems; collaboration processes are supported by such smart (learning) systems.
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Against that background we would like to give you a definition of CIL and a brief description of the project context respectively aim of the project:
Collaborative Interactive Learning (CIL) describes a new generation of learning systems based on novel techniques. Learning in such CIL based learning systems is:
(1.) Collaborative - in the sense that various humans (experts or non-experts, depending on the application) and/or smart systems collaborate to solve certain problems (e.g., problems that they cannot solve by their own), and
(2.) Interactive in the sense that there is an information and knowledge flow not only from humans to the smart systems but also vice versa in various, more or less complex ways.
CONTEXT & GOAL:
Technical systems are solving increasingly complex tasks with the help of computers. Originally, these systems had been drawn up for particular tasks and operating conditions and were limited to those during runtime. Nowadays, they are able to adapt to new situations, learn from observations and optimize themselves. For that reason, they are often called smart or intelligent. In the future, there will be more and more applications where not all of the data necessary for learning can be provided - even not for self-learning systems at time of design. A simple adaptation (e.g. of parameters) during runtime fails to be sufficient, as well. Reasons are, for instance, the required amount of data, the time needed for acquisition or financial costs and, in particular, the fact that while duration these systems are being confronted with situations not known at the time of development (situations not able to be known, inherently). What is required, hence, is a completely new kind of smart systems with a lifelong ability to learn (corresponding to the aggregate service life of the system) in uncertain and temporal variable environments. These systems need to operate intensively autonomic, by evaluating their own knowledge, independently procuring resources (humans, other systems, internet etc.) or connecting with them, rating information of others (e.g. with respect to currentness) and thereby using different machine learning methods (e.g. Collaborative Learning or Active Learning).
The aim of this project is the investigation of a class of entirely new technologies for the development of systems outlined above and which we identify as Collaborative Interactive Learning (CIL). These machine learning methods are ‘collaborative’ in the sense that several systems cooperate among themselves and with humans, in order to mutually solve problems (including those not capable of being solved on their own). Also, they are ‘interactive’ as there will be an actively animated and regular flow of knowledge and information - not only between these technical systems but also between systems and humans in various ways. Potential applications of CIL have been identified in many areas: cyber-physical systems that are learning from each other, teams of autonomic robots, cooperating autonomic vehicles, distributed systems for intrusion detection in computer networks, design of cooperation mechanisms for the solution of tasks employing processes of Collaboration Engineering, Crowdsourcing in order to use an expertise of an indefinite mass of people etc.