A gradient-based artificial immune system applied to optimal power flow problems
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Motion feasibility of multi-agent formations
IEEE Transactions on Robotics
A multiagent model of the UK market in electricity generation
IEEE Transactions on Evolutionary Computation
Review Article: Recent Advances in Artificial Immune Systems: Models and Applications
Applied Soft Computing
| Hi-index | 0.00 |
When a set of heterogeneous agents is considered to solve different kinds of problems, it is very challenging to specify the necessary number of elements, which functionally of each one will be used and the schedule of these actions in order to solve these problems. To deal with scenarios like this, the present article suggests an innovation at the Intelligent Agent Theory, a new concept called Dynamic Polymorphic Agent (DPA). This approach implies on the dynamic generation of one agent, built from the cooperation of existing agents and specific to fulfill the demanding task. To create this new entity, a monitor identifies and reads information regarding the functionalities of available agents present in the scene and, when a new problem is presented, it generates a task list to solve it. This list and the agents whose functionalities are necessary to solve the problem generate the new polymorphic agent. To fulfill this approach, two major paradigms are used: Aspect-Oriented Program (AOP) and Artificial Immune System (AIS).