This chapter introduces a suite of technologies for building complex, adaptive systems. It is based in the multi-agent systems paradigm and uses the Organization Model for Adaptive Computational Systems (OMACS). OMACS defines the knowledge needed about a system’s structure and capabilities to allow it to reorganize at runtime in the face of a changing environment and its agent’s capabilities. However, the OMACS model is only useful if it is supported by a set of methodologies, techniques, and architectures that allow it to be implemented effectively on a wide variety of systems. To this end, this chapter presents a suite of technologies including (1) the Organization-based Multiagent Systems Engineering (O-MaSE) methodology, (2) a set of policy specification techniques that allow an OMACS system to remain flexible while still providing guidance, and (3) a set of architectures and algorithms used to implement OMACSbased systems. The chapter also includes the presentation of a small OMACS-based system.
Computational organization theory uses mathematical and computational techniques to study both human and artificial organizations (Carley 1999). While organizational concepts are not exclusive to computational organization theory, results from the field are illuminating. Specifically, they suggest that organizations tend to adapt to increase performance or efficiency, that “the most successful organizations tend to be highly flexible” (Carley 1998), and that the best organizational designs are highly application and situation dependent (Carley, 1995). Recently, the notion of separating the agents populating a multiagent system from the system organization (Zambonelli, Jennings, & Woodridge, 2001) has become well-accepted. While agents play roles within the organization, they do not constitute the organization. The organization itself is part of the agent’s environment and defines the social setting in which the agent must exist. An organization includes organizational structures as well as policies, which define the requirements for system creation and operation.
Key Terms in this Chapter
Organization-Based Agent (OBA) Architecture: an architecture for implementing agents capable of reasoning within an OMACS organization.
Reorganization: The transition from one organizational state to another.
Organization Model for Adaptive Computational Systems (OMACS): A model that defines the knowledge needed about a system’s structure and capabilities to allow it to reorganize at runtime in the face of a changing environment and its agent’s capabilities.
Organization-Based Multiagent Systems Engineering (O-MaSE): A framework for creating compliant processes that support the development of OMACS-based systems
Capability: An atomic entities used to define a skill or capacity of agents.
Agent: An entity that perceives and can perform actions upon its environment, which includes humans as well as artificial (hardware or software) entities.
Role: Defines a position within an organization whose behavior is expected to achieve a particular goal or set of goals.
Policy: A specification of desired system behavior that can be used to specify either (1) what the system should do or (2) what the system should not do.
Goal: A desirable state of the world or the objective of a computational process.
Goal Model for Dynamic Systems (GMoDS): a set of models for capturing system level goals and for using those goals at runtime to allow the system to adapt to dynamic problems and environments.