Webinar "Coding for AI: Fuzzy logic"
Webinar for STEM teachers who are interested to learn about the concept of "fuzzy logic".
Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false. By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1.
Fuzzy logic is based on the observation that people make decisions based on imprecise and non-numerical information. Fuzzy models or sets are mathematical means of representing vagueness and imprecise information (hence the term fuzzy). These models have the capability of recognizing, representing, manipulating, interpreting, and utilizing data and information that are vague and lack certainty.
Fuzzy logic has been applied to many fields, from control theory to artificial intelligence and has been successfully used in numerous fields such as control systems engineering, image processing, power engineering, industrial automation, robotics, consumer electronics, and optimization. This branch of mathematics has instilled new life into scientific fields that have been dormant for a long time.
Astrinos Tsoutsoudakis is a science teacher in state upper secondary schools and a STEM trainer in Erasmus+ projects. He lives in Heraklion on Crete Island in Greece and his current job includes supporting primary and secondary school teachers in their experimental science teaching. He has recently been honored by becoming one of Science on Stage Europe Ambassadors.
Ioannis Tzagkarakis is a software developer and a computer science and robotics teacher in private sector schools and Erasmus+ projects. He has participated as a team mentor in various competitions and has been honored with national and international awards.