TOWARD A DESIGN ONTOLOGY FOR SELF-ORGANIZING SYSTEMS

Many designers have demonstrated self-organizing systems of simple agents performing useful collective tasks such as shape formation or foraging. These systems draw inspiration from biology, engineering, economics and other diverse research areas. The great diversity of approaches has led to a large body of applications and simulations. The lack of unity among different approaches, however, leads to challenges in system integration, knowledge transfer, and modeling. With a shared vocabulary, designers could create a common conceptualization of the self-organizing systems design process and more easily share discoveries across application domains. To this end, we propose an ontology that covers the design and deployment of self-organizing systems with an emphasis on function, form, and behavior at the agent, group, and system levels of analysis, with particular emphasis on the behavioral design of agents. INTRODUCTION The theory of design of self-organizing (SO) systems is still in its nascent stages. Many designers are interested in the function, behavior, and form of such systems, but do not have a large bank of analogous systems to refer to when mapping between behavior and form, or between local and global levels of system behavior. Although various SO systems have been demonstrated, most researchers have taken an ad hoc approach to their design, demonstrating specific successes but not general methodologies [1]. Ontologies are useful tools for organizing a domain of knowledge. With a regimented ontology of the SO system design process, various successful systems can be categorized, and their important self-organizing mechanisms can be documented for possible adoption for other, similar functions. An ontology is a knowledge structure applied to a domain of interest. Ontologies define formal languages, easing information transfer and clarifying semantics. They are abstract, detailing only the important (to specific users) details of a domain, and should be “explicit,” giving a precise definition of the concepts and relationships contained within the ontology [2]. Ontologies are often used for consistency in knowledge transfer between cooperating entities, whether they be humans [3] or computer agents [4]. In our research, as an attempt to organize lessons learned by diverse studies on the use of self-organization, with a particular emphasis on the use of self-organization as a tool in engineering design, we are developing ontology for designing self-organizing systems. This paper reports our initial step in building a FBS (function, behavior and structure) based ontology in the self-organizing systems context. This ontology draws a distinction with the traditional design process by focusing on the three levels of system architecture and defining the key characteristics of function, behavior and structure at these levels. By enumerating the key concepts in the selforganizing system design process, we are able to identify the mappings between certain concepts where most the design work takes place, regardless of the system’s application domain or the designer’s field of expertise. A case study on the design of a self-organizing foraging system using the mappings described in the ontology is presented along with example applications of the terminology to self-organizing systems from the literature. RELATED WORK Researchers are currently making a similar effort in the biological sciences, and their work can inform our own due to similarities that self-organizing systems show to biological systems, and because their goals of knowledge capture and