setting (see the Structural Layer previously mentioned) are additionally concerned with problems
related to argument construction and defeat discovery. In many application scenarios, knowledge is represented as facts and rules or, more generally, as formulas in some logic. In order to apply argumentation
technology, arguments have to be constructed by
combining formulas and conflicts between different
arguments have to be detected. 13, 14, 15, 16 Many systems for structured argumentation generate argumentation graphs such as the one shown in figure 2
as output and use abstract argumentation solvers for
the actual determination of acceptable arguments.
However, as actual application contexts may require
the user to specify facts and rules rather than the
induced arguments, systems for structured argumentation are a key element for the adoption of argumentation technology in actual applications.
In order to evaluate the state of the art of argu-
mentation solvers, the International Competition on
Computational Models of Argumentation (ICCMA) 17
was initiated in 2014 and organized its first contest in
2015 (Thimm et al. 2016). For the first contest, the
focus was on problems related to abstract argumenta-
tion and solvers were evaluated based on their run-
time performance for computing extensions or decid-
ing on acceptance of arguments with respect to
complete, preferred, stable, and grounded semantics
of abstract argumentation, (compare with Dunn
). There were 18 participating systems and the
best performing ones achieved significant improve-
ments with respect to the state of the art. Based on
these encouraging results, a second contest will be
held in 2017.
Developing artificial tools that capture the human
ability to argue is an ambitious research goal, and it
may ultimately prove to be as difficult as developing
AI in general.
As described in this article, current research
addresses a range of applications like law, medicine, e-government, debating, where argument-based
approaches have shown to be beneficial for intelligent activities like sense making and decision making. These areas witness an increasing integration of
proactive support and automated reasoning capabilities, complementing the functionalities offered by
other useful but more passive tools like argument
Even more sophisticated roles for artificial argumentation tools are sought in the medium term and
are the subject of recent research initiatives. For
instance, there is a growing interest in developing
computational persuasion systems able to assist people in making better choices in their daily activities.
Consider scenarios such as a doctor persuading a
patient to drink less alcohol, a road safety expert per-
Figure 3. Arvina.