Information Technology Reference
In-Depth Information
Section 2 motivates the delegating process of tasks to the environment for commu-
nication and simulation and introduces an illustrative example with different examples
issued of a crisis management application. Section 3 presents the environment model.
Section 4 provides a theoretical evaluation. In section 5, we provide an empirical eval-
uation, and we conclude in section 6.
2
Motivations
2.1
Communication
Recent research on multi-party communications [3,13] shows how multi-agent commu-
nications can take advantage of the complexity of the human communication process.
The main issue in supporting MPC is to take into account dyadic interaction (one to
one), group interaction (one to many) and overhearing (many to one/many) within the
same interaction process. The sender does not know all the agents that might be inter-
ested in its messages. For example, an agent can listen to messages without the agree-
ment/knowledge of the sender through overhearing. For a recipient, the usefulness of a
message may depend on the context of the sender, the context of the message, and the
context of the recipient itself.
These challenges are related to the way the recipients are chosen. MPC requires
knowledge of the needs of both the sender and the recipients. From the sender viewpoint
(direct interaction), it is a connection problem: which agents are related to my message?
The problem is to map the senders needs (information, capabilities, resources, ...) to the
address of related agents. From the recipient viewpoint (indirect interaction), it is a data
extraction problem: which messages are related to me? The problem is to map the re-
cipients needs to the content of the messages. For each message, these problems have
to be simultaneously solved by the communication infrastructure. The environment is
able to solve these problems by mediating the communication in order to find all the
receivers of each message. Nevertheless, in the cognitive agents community, few works
explicitly present the environment as an interaction support. For direct interaction, the
environment is often associated to an infrastructure that supports point to point commu-
nication. For indirect interaction, cognitive agents use specific services that are based
on the management of a shared collection of data (
e.g.
[11]) that may be understood as a
part of the environment. There is therefore a separation between the solutions to realize
direct and indirect interaction although the environment provides a suitable framework
to unify them [12].
If the computation of the context does not take into account ambient conditions, it
can classically be done inside the agents. This solution implies that the agents receive
all messages and filter them. An evaluation of the environment support consists in the
cost comparison of the context filtering either in each agent after the reception or in the
environment during the transmission process.
2.2
Agent-Based Simulation
In a simulation, the scheduling policy defines the activation order of the agents. Once
activated, the agents behave according to their context. How the agents are activated and
