JuzzyPy ― A Python Library to Create Type―1, Interval Type-2 and General Type-2 Fuzzy Logic Systems

We present JuzzyPy, a Python based fuzzy logic toolkit enabling the creation of type-1, interval type-2, and general type-2 fuzzy logic systems. Fuzzy logic systems are being applied in disciplines across engineering and sectors such as cyber-security and autonomous systems, where an increasing focus on interpretability and trust is re-emphasising a focus on rule-based systems. This highlights the value of broadly accessible software resources to support both experts and non-experts in efficiently designing fuzzy systems. Python is currently the most popular programming language in the world. JuzzyPy is the first library capable of supporting the development of general type-2 systems in Python, facilitating access to these systems across engineering disciplines. In this paper we delve into the ability of the toolkit and explore its implementation. We hope that this allows for further accessibility in the use of fuzzy logic systems and provides a basis for developers, practitioners and researchers to collaborate on scientific advancement of the field and the tackling of real-world problems.