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Computational argumentation is a promising research area, yet there is a gap between theoretical contributions and practical applications. Bridging this gap could potentially raise interest in this topic even more. We argue that one part of the bridge could be an open-source package of implementations of argumentation algorithms, visualised in a web interface. Therefore we present a new release of PyArg, providing various new argumentation-based functionalities – including multiple generators, a learning environment, implementations of theoretical papers and a showcase of a practical application – in a new interface with improved accessibility.

The relatively young area of forgetting is concerned with the removal of selective information, while preserving other knowledge. This might be useful or even necessary, for example, to simplify a knowledge base or to tend legal requests. In the last few years, there has been an ample amount of research in the field, in particular with respect to logic programs, spanning from theoretical considerations to more practical applications, starting at the conceptual proposal of forgetting, to suggestions of properties that should be satisfied, followed by characterizations of abstract classes of operators that satisfy these properties, and finally the definition of concrete forgetting procedures. In this work we present novel Python implementations of all the forgetting procedures that have been proposed to date on logic programs. We provide them in a web interface, and hope to thereby give anybody who is interested a low-barrier overview of the landscape.