  Weighted bipolar argumentation frameworks allow modeling decision problems
and online discussions by defining arguments and their relationships. The
strength of arguments can be computed based on an initial weight and the
strength of attacking and supporting arguments. While previous approaches
assumed an acyclic argumentation graph and successively set arguments' strength
based on the strength of their parents, recently continuous dynamical systems
have been proposed as an alternative. Continuous models update arguments'
strength simultaneously and continuously. While there are currently no
analytical guarantees for convergence in general graphs, experiments show that
continuous models can converge quickly in large cyclic graphs with thousands of
arguments. Here, we focus on the high-level ideas of this approach and explain
key results and applications. We also introduce Attractor, a Java library that
can be used to solve weighted bipolar argumentation problems. Attractor
contains implementations of several discrete and continuous models and
numerical algorithms to compute solutions. It also provides base classes that
can be used to implement, to evaluate and to compare continuous models easily.
