Agent-based simulation of adaptive organizational structures to environmental change

Abstract

This paper proposes an agent-based simulation model for analyzing adaptive processes of organizational structures to environmental changes. The model is based on a framework of computational organization theory (COT) and performed using the method of inverse simulation with genetic algorithm. The model specifies an activity process in organization that is composed of tasks, agents and environments. The roles of agents: normal and leader, are defined based on some basic tasks of agents: recognizing tasks from environment, sharing knowledge required for processing tasks, and coordinating tasks among agents. Organizational structures are distinguished according to the configuration of the roles of agents resolving the tasks recognized. Adaptation process is represented as learning process of agents' internal models of environments. Environments are expressed as task generators and fall into 5 types. This paper shows some fundamental relationships between organizational structures and dynamically changing environments.