Smart Edges 69
To successfully allocate the tasks, we need to know the skills of
each of the agents, decompose a problem into sub-problems, distribute
the solving activities to the appropriate agents and, as required,
redistribute those activities dynamically.
Task allocation models can be classified into two categories:
– centralized allocation: in this modular approach, an agent breaks
down a problem into sub-problems and distributes those sub-problems
to other agents, which are subordinate to the original agent. In this
case, the actions are consistent, but there is a problem of reliability
and extensibility. In addition, an agent is entirely dedicated to the
distribution of tasks. Thus, the system is not used to the full extent of
its capabilities;
– decentralized, or distributed, allocation: each agent is capable of
breaking up its own problem into sub-problems and thus distributing
the tasks associated therewith. All the agents carry the same weight in
the decision-making process. This type of allocation is appropriate for
applications which already have a distributed structure. The reliability
and the possibility of extension are better than with the previous
model, but it is more difficult to maintain consistency.
Three types of methods may be employed to decompose a
problem:
– static: with each agent knowing the skills of the other agents, the
sub-problems can be attributed to the best-qualified agents;
– dynamic: the agents work together to distribute the sub-problems
in the most effective way possible;
– mixed: each agent is aware of the skills of the other agents, but
this knowledge is periodically updated.
The autonomy of the agents is founded on the concept of
intentionality. We can differentiate intention in an action from the
intention to commit an action in the future. In the latter case, we have
a standing goal. In order for an agent to have the intention to perform
an action, that agent must believe that the action is possible, envisage
committing to performing it, estimate that if certain conditions are
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To successfully allocate the tasks, we need to know the skills of
each of the agents, decompose a problem into sub-problems, distribute
the solving activities to the appropriate agents and, as required,
redistribute those activities dynamically.
Task allocation models can be classified into two categories:
– centralized allocation: in this modular approach, an agent breaks
down a problem into sub-problems and distributes those sub-problems
to other agents, which are subordinate to the original agent. In this
case, the actions are consistent, but there is a problem of reliability
and extensibility. In addition, an agent is entirely dedicated to the
distribution of tasks. Thus, the system is not used to the full extent of
its capabilities;
– decentralized, or distributed, allocation: each agent is capable of
breaking up its own problem into sub-problems and thus distributing
the tasks associated therewith. All the agents carry the same weight in
the decision-making process. This type of allocation is appropriate for
applications which already have a distributed structure. The reliability
and the possibility of extension are better than with the previous
model, but it is more difficult to maintain consistency.
Three types of methods may be employed to decompose a
problem:
– static: with each agent knowing the skills of the other agents, the
sub-problems can be attributed to the best-qualified agents;
– dynamic: the agents work together to distribute the sub-problems
in the most effective way possible;
– mixed: each agent is aware of the skills of the other agents, but
this knowledge is periodically updated.
The autonomy of the agents is founded on the concept of
intentionality. We can differentiate intention in an action from the
intention to commit an action in the future. In the latter case, we have
a standing goal. In order for an agent to have the intention to perform
an action, that agent must believe that the action is possible, envisage
committing to performing it, estimate that if certain conditions are
www.it-ebooks.info