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ABA Learning via ASP
Recently, ABA Learning has been proposed as a form of symbolic machine learning for drawing Assumption-Based Argumentation frameworks from background knowledge and positive and negative examples.
Learning Assumption-based Argumentation Frameworks
We present a general strategy that applies the transformation rules in a suitable order to learn stratified frameworks, and we also propose a variant that handles the non-stratified case.
Ontology-based Representation and Reasoning on Process Models: A Logic Programming Approach
We propose a framework grounded in Logic Programming for representing and reasoning about business processes from both the procedural and ontological point of views.
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