tribute to the feasibility of comparing
between different automated agents
when matched with people. Preliminary work on this facet is already under
way by Hindriks et al.
13 and Oshrat et
28 however, we believe the aspect of
generality should be addressed more
by researchers. In this respect, metrics
should be designed to allow a comparison between agents. To achieve this,
some of the questions described earlier regarding “what constitutes a good
negotiator agent?” should be answered
In addition, argumentation, though
dealt with in the past, still poses a challenge for researchers in this field. For
example, about 10 years ago Kraus23
presented argumentation as an iterative process emerging from exchanges
among agents to persuade each other
and bring about a change in intentions. They developed a formal logic
that forms a basis for the development
of a formal axiomatization system for
argumentation. In particular, Kraus
identified argumentation categories
in human negotiations and demonstrated how the logic can be used to
specify argument formulations and
evaluations. Finally, they developed
an agent that was implemented, based
on the logical model.
However, this agent was not
matched with human negotiators.
Moreover, there are several open research questions associated with how
to integrate the argumentation model
into automated negotiators. Since
the argumentation module is based
on logic and thus is time consuming,
a more efficient approach should be
used. In addition, the current model
is built on a very complex model of the
opponent and therefore should be incorporated in the automated negotiator’s model of the opponent. In order
to facilitate the design, a mapping between the logical model and the utili-ty-based model is required.
To conclude, in recent years the
field of automated negotiators that
can proficiently negotiate with human
players has received much needed
focus and the results are encouraging. We presented several of these
automated negotiators and showed
it is indeed possible to design such
proficient agents. Nonetheless, there
are still challenges that pose interest-
ing research questions that must be
pursued and exciting work is still very
much in progress.
We thank David Sarne, Ya’akov (Kobi)
Gal, and the anonymous referees for
their helpful remarks and suggestions.
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this research is based upon work supported in part by
the u.s. army research laboratory and the u.s. army
research office under grant number W911nF-08-1-0144
and under nsF grant 0705587.
Raz Lin is a Postdoctoral Fellow in the computer science
department at bar-Ilan university, ramat-Gan, Israel.
Sarit Kraus is a professor of computer science
department at bar-Ilan university, ramat-Gan, Israel,
and adjunct professor in the Institute for advanced
Computer studies at the university of Maryland, College