Meaning Negotiation as Inference
  Meaning negotiation (MN) is the general process with which agents reach an
agreement about the meaning of a set of terms. Artificial Intelligence scholars
have dealt with the problem of MN by means of argumentations schemes, beliefs
merging and information fusion operators, and ontology alignment but the
proposed approaches depend upon the number of participants. In this paper, we
give a general model of MN for an arbitrary number of agents, in which each
participant discusses with the others her viewpoint by exhibiting it in an
actual set of constraints on the meaning of the negotiated terms. We call this
presentation of individual viewpoints an angle. The agents do not aim at
forming a common viewpoint but, instead, at agreeing about an acceptable common
angle. We analyze separately the process of MN by two agents (\emph{bilateral}
or \emph{pairwise} MN) and by more than two agents (\emph{multiparty} MN), and
we use game theoretic models to understand how the process develops in both
cases: the models are Bargaining Game for bilateral MN and English Auction for
multiparty MN. We formalize the process of reaching such an agreement by giving
a deduction system that comprises of rules that are consistent and adequate for
representing MN.
