In this paper, we propose an interaction model which
allows more realistic interactions for simulations of
human societies and limits the communication cost.
Interaction is a central concept when designing a multiagent
system. Classically, interaction between two
agents contains two elements: communication and the
action which is the result of this information exchange.
This view of interaction has underpinned most research
in the multi-agent domain. However, if we draw an
analogy with human behavior, the notion of interaction
is more complex and we show that the classical ways of
interaction managing are not adapted. To reach this
objective, the environment could be used to mediate
interaction between agents. A toy problem shows that
our proposition helps the agents to adapt their
perception of communications in the light of their
interest and limits the communication cost in case of
complex interactions between agents. A real application
stemming from the transportation domain illustrates the
use of our proposition to help agents to adapt their
behavior to the context.
[1]
Katia P. Sycara,et al.
Middle-Agents for the Internet
,
1997,
IJCAI.
[2]
Jacques Ferber,et al.
Reactive distributed artificial intelligence: principles and applications
,
1996
.
[3]
Flavien Balbo,et al.
Toward a Multi-agent Modelling Approach for Urban Public Transportation Systems
,
2001,
ESAW.
[4]
Liz Sonenberg,et al.
Enhancing Multi-Agent Based Simulation with Human-Like Decision Making Strategies
,
2000,
MABS.
[5]
Gerhard Weiss,et al.
Multiagent systems: a modern approach to distributed artificial intelligence
,
1999
.
[6]
Ingo Schulz-Schaeffer,et al.
Generalized Media of Interaction and Inter-Agent Coordination
,
1997
.
[7]
Yves Demazeau,et al.
FROM INTERACTIONS TO COLLECTIVE BEHAVIOUR IN AGENT-BASED SYSTEMS
,
1995
.
[8]
Julie Dugdale,et al.
A Pragmatic Development of a Computer Simulation of an Emergency Call Centre
,
2000,
COOP.