DE VIDIGAL, Michael Charles Andrew Curado Fleury; http://lattes.cnpq.br/4087189661400095
Resumo:
When multiple agents with different characteristics are considered to solve a
set of problems, it is very challenging to specify the number of agents, the specific
function of each one to be used, and the schedule of these actions in order to solve
these problems. Different situations may demand different sets of agents with specific
knowledge regarding how to solve each problem. To deal with scenarios like this, the
present article suggests an innovation at the Intelligent Agent Theory, a new concept
called Intelligent Dynamic Polymorphic Agent (IDPA). The IDPA has the goal of trying
to find the minimum set of resources and agents (each one with its own
characteristics) to plan and execute specific problems using AI planning. By on-line
actualization, the IDPA architecture allows the quest for available agents present in
the system and being feed by information about their respective domains. Using this
knowledge, the system uses a predefined heuristic model to dynamically assist the
planner obtaining a plan with a reduced number of resources. It also identifies and
dispatches the necessary agents in order to carry out the plan. After this
identification, the agents merge with the entity called APDI, which, through
polymorphism, is capable of accomplish the initial task Another benefit of this
methodology is that, due to its dynamic behavior, it is possible to change the original
plan by the advent of an unexpected problem, even if the plan is being already
executed.