Ant Clustering Algorithm In Cooperation Of Agents

In a dynamic environment that different agent are present, a crucial problem is to find agents with similar skills efficiently in order to perform a certain task that can not be done by single agents or even a small group of agents. This can be done via global communication, but in case where only local communication are possible, the problem changes into finding clusters of homo-skill agent via local communication and limited sense potency .T he study of ant colonies behavior and their self-organizing capabilities is of interest to solve current problem, it provides models of distributed adaptive organization, which are useful to solve difficult optimization, classification, and distributed control problems, among others. In this paper, we propose an ant clustering algorithm (AC) and Ant Sleeping Model (ASM) applied to discover groups of homo-skill agents in order to solve one problem in cooperation of agents. An Example paradigm is presented to demonstrate the implementation and its results are shown.