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1. Every time an addressee receives a new bit of information, she checks if it
fits what she already believes. If this is the case, nothing happens, otherwise,
if the new information uncovers some incoherence, she has to react to avoid
cognitive dissonance;
2. She faces two alternatives: ( a ) either to reject the new information because
she does not trust the source enough, to start a revision of her own opinions.
In that case, the addressee can reply with an argument that attacks the
new information; ( b ) or to accept the new information because she trusts
the source enough, to start a coherence checking and allow for a fine-grained
process of opinion revision;
3. The source can react as well to the addressee's reaction: if the addressee de-
cides to refuse the new information, the source can produce arguments to in-
ject trust in the addressee, like exhibiting a social status which demonstrates
competences on the subject matter. Otherwise, the source can produce ar-
guments to persuade the addressee that the new information is logical and
coherent, or to rebut the addressee's reply.
4. Both addressee and source may have to revise their own opinions while in-
volved in such a turn-taking interaction, until: ( a ) addressee (or source)
revises her own opinions; ( b ) they decide to stop arguing because they do
not trust each other.
Such a turn-taking interaction between communicants is called a “dialogue”. As
said before, our agents argue through simulated dialogues. Before discussing how
such a simulated role-taking process unfolds, we introduce how agents represent
their knowledge by means of abstract argumentation. In computational abstract
argumentation, as defined by Dung [9], an “Argumentation Framework” ( AF )
is defined as a pair
A
,
R
A
R
is a
binary attacks relation over arguments, R⊆A×A , with α → β ∈R interpreted
as “argument α attacks argument β .” In other words, an AF is a network of
arguments, where links represent attack relations between arguments. Consider
this simple exchange between two discussants, D 1 and D 2 :
,where
is a set of atomic arguments and
- D 1 : My government cannot negotiate with your government because your
government doesnt even recognize my government ( a ).
- D 2 : Your government doesn't recognize my government either ( b ).
- D 1 : But your government is a terrorist government ( c ).
Abstract argumentation formalizes these positions through a network represen-
tation, as shown in Figure 1. Once the network has been generated, abstract
argumentation analyzes it by means of semantics [6], i.e. set of rules used to
identify “coherent” subsets of arguments. Semantics may range from very cred-
ulous to very skeptical ones. Each coherent set of arguments, according to the
correspondent semantics, is called an “extension” of
. Some well-known seman-
tics defined by Dung are the admissible and the complete semantics. To illustrate
the rules imposed by these semantics, let us consider a set S of arguments, S
A
⊆A
:
 
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