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We propose a formal model for argumentation-based dialogues between agents, using assumption-based argumentation (ABA) as the underlying argumentation framework.
The underlying argumentation theory is Dung's one: each argumentation system gives both a set of arguments and the way they interact (i.e., attack or non-attack) according to the corresponding agent.
The underlying argumentation draws upon a number of issues.
Fortunately, the details of this formalization need not be communicated to the end user and our initial evaluation (see Section 7) adds weight to our view that the underlying argumentation reasoning is accessible and helpful to biologists.
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The three assumptions underlying such argumentations are that African migration is: high and increasing; mainly directed towards Europe; and driven by poverty and violence.
It should be noted, therefore, that underlying More's argumentation is a commitment to the belief that matter is essentially passive (capable only of inertial motions), and that only immaterial entities are active.
Due to the dynamics of underlying theories, argument construction is not a monotonic process, which is different from the existing argumentation framework where arguments are constructed incrementally.
The development of the argumentation theories underlying the systems has culminated in the logical system DefLog that formalizes the interpretation of prima facie justified assumptions.
And for all the professed feminism scattered throughout, the assumption underlying much of this argumentation seems to be that the world would be a better place if women would simply stay home and care for their own children, do their own housework and tend to their own aging parents without relying on less fortunate women to help.
The concept underlying the "Dynamic Programming Argumentation Reasoning Tool" [42,115] is based on dynamic programming, where the instance is decomposed before solving (see Section 4.3).
The aims of the analysis were: (A) to identify implicit biological background assumptions that underlie the scientific argumentation as well as research hypotheses about risk of GM stacks, and (B) to test whether differing biological background assumptions are central to the opposing positions.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com