A capabilities-based model for adaptive organizations

  • Authors:
  • Scott A. Deloach;Walamitien H. Oyenan;Eric T. Matson

  • Affiliations:
  • Department of Computing & Information Sciences, Kansas State University, Manhattan, USA 66506;Department of Computing & Information Sciences, Kansas State University, Manhattan, USA 66506;Department of Computer Science and Engineering, Wright State University, Dayton, USA

  • Venue:
  • Autonomous Agents and Multi-Agent Systems
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Multiagent systems have become popular over the last few years for building complex, adaptive systems in a distributed, heterogeneous setting. Multiagent systems tend to be more robust and, in many cases, more efficient than single monolithic applications. However, unpredictable application environments make multiagent systems susceptible to individual failures that can significantly reduce its ability to accomplish its overall goal. The problem is that multiagent systems are typically designed to work within a limited set of configurations. Even when the system possesses the resources and computational power to accomplish its goal, it may be constrained by its own structure and knowledge of its member's capabilities. To overcome these problems, we are developing a framework that allows the system to design its own organization at runtime. This paper presents a key component of that framework, a metamodel for multiagent organizations named the Organization Model for Adaptive Computational Systems. This model defines the requisite knowledge of a system's organizational structure and capabilities that will allow it to reorganize at runtime and enable it to achieve its goals effectively in the face of a changing environment and its agent's capabilities.