The CMNA workshop series focuses on the general issue of modelling “natural” argumentation.
However, to celebrate our co-location with COMMA, this year we have introduced a special theme on exploration of the space between computational and natural models of argument. Our theme should be interpreted broadly, to reflect the wide range of approaches to recognising, formalising, and understanding the richness of real-world reasoning and communication processes within computational models.
Nothwithstanding the special theme, we also solicit contributions addressing, but not limited to, the following areas of interest:
Contributions are solicited addressing, but not limited to, the following areas of interest:
- The characteristics of “natural” arguments (e.g. ontological aspects, cognitive issues, legal aspects).
- The linguistic characteristics of natural argumentation, including discourse markers, sentence format, referring expressions, and style.
- The generation of natural argument
- Corpus argumentation results and techniques
- Argumentation mining
- Models of natural legal argument
- Rhetoric and affect: the role of emotions, personalities, etc. in argumentation.
- The roles of licentiousness and deceit and the ethical implications of implemented systems demonstrating such features.
- Natural argumentation in multi-agent systems.
- Methods to better convey the structure of complex argument, including representation and summarisation.
- Natural argumentation and media: visual arguments, multi-modal arguments, spoken arguments.
- Evaluative arguments and their application in AI systems (such as decision-support and advice-giving).
- Non-monotonic, defeasible and uncertain argumentation.
- The computational use of models from informal logic and argumentation theory.
- Computer supported collaborative argumentation, for pedagogy, e-democracy and public debate.
- Tools for interacting with structures of argument.
- Applications of argumentation based systems.
We’ve prided ourselves in operating CMNA as a “broad church” and aiming for inclusiveness so if you’re unsure of whether CMNA is a good fit for your work you can: