Problem Solving by Negotiation among Autonomous Knowledge-Processing Systems
E.Suzuki, K.Hori, S.Ohsuga, P.Morizet-Mahoudeaux
Abstract
Distributed expert systems have several advantages compared with
ordinary expert systems. Research on such systems belongs to the field
of cooperative problem solving, which is a sub-field of distributed
artificial intelligence. Cooperative problem solving can be divided
into three stages: (1) problem decomposition, (2) subproblem solution,
and (3) answer synthesis. Several studies have addressed to the
general domain-independent model of the first and second
points. However, for the second and third points, most studies have
addressed only specific cases of distributed expert systems and have
insisted on the generality of their method. Few of these works have
presented general domain-independent architectures and their
implementation. In order to cope with this problem, we present CoKBS:
an architecture for managing several autonomous knowledge-processing
systems (called agents hereafter). CoKBS has been implemented with the
metaphor of negotiation among human experts. In CoKBS, the solution to
the problem at work is obtained after negotiation between the involved
agents. The agent which is in charge of the problem at work selects
two agents and the solution is obtained after a negotiation procedure
has been carried out between the two agents. During the negotiation
procedure each agent may update dynamically his beliefs, his
perspective, his own model, as well as his model of the other agent.
The behavior of the agent during the negotiation is determined by his
set of meta rules and domain-independent meta rules are supplied by
the system. The architecture has been tested on a simple application
with an experimental system.
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