Loading

Research on Multi-Agent Experiment in Clustering
Mohammed Ali Shaik1, T. Sampath Kumar2, P. Praveen3, R. Vijayaprakash4

1Mohammed Ali Shaik, Ph.D Research Scholor, Assistant Professor, Department of Computer Science & Engineering, APJ Abdul Kalam University, Indore, (M.P), India.
2T. Sampath Kumar, Assistant Professor, Department of Computer Science & Engineering, S R Engineering College, Warangal (Telangana), India.
3Dr. P. Praveen, Assistant Professor, Department of Computer Science & Engineering, S R Engineering College, Warangal (Telangana), India.
4Dr. R. Vijayaprakash, Professor, Department of Computer Science & Engineering, S R Engineering College, Warangal (Telangana), India.
Manuscript received on 09 June 2019 | Revised Manuscript received on 30 June 2019 | Manuscript Published on 04 July 2019 | PP: 1126-1129 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A12100681S419/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Clustering is the process of classification of data in any of the emerging fields in present day scenario. In this paper we have proposed a framework for “multi-agent based clustering (MAS)” which is based on the working methodology of individual agents that initiate to dissolve a cluster. The major identification in this paper is once a cluster is created by an agent distinct types of agents will communicate and send messages for performing a task given to them, this process continues till the dissolving of cluster. An agent has the capability to either create a cluster or kill the cluster. And agents can even perform Inter cluster communication (ICC) between various clusters that are created as per requirement or necessity. We used K-means and KNN algorithms and shown that ICC can improve a clustering environment.
Keywords: Multi-Agent Data Mining, Clustering, Inter Cluster Communication.
Scope of the Article: Clustering