This paper presents a new architecture of a classifier system for
learning in virtual environments. The model will be integrated in our
multi-user platform to provide interaction between intelligent agents
and user clones. An agent is an autonomous entity equipped with sensors
and effectors. Its behavior is guided by rewards coming from the
environment that produce rules called classifiers. The knowledge is
shared between agents by using the “sending-message” protocol to
increase the global efficiency of the group. The classifier system is
specially adapted to a multi-task environment and incorporates a
short-term memory to record the recent events of the simulation. These
ideas have been implemented and used to develop a virtual soccer where
the user plays with autonomous agents that combine communication and
evolution.
