Notes on Organization Design from the Perspective of AI Les Gasser Short Paper for AAAI COD Symposium An AIoriented approach to organization modeling, analysis, and design entails building specific, computational models of things that we often (informally) call organizations". Such models will be formal in the sense that they are computational---that is, they will have some defined semantics in the sense that a computer will take specific actions when operating upon them in a design or analysis process [Gasser et al. 1993]. Presently, we seem to have a tradeoffbetween clearl pragmatically and computationally defining the concept of"organization" on the one hand, and capturing the richness of features of interesting (e.g. The aim of this paper is to begin to think through the needs a computational theory of organization that is clear, rich, and representative, and yet still useful for both computational analysis and design. Some well-known attempts to define organization in AI are direct, simple and mundane---these include approaches such as those used in the UMASS DVMT [Durfee et al. 1987] and our own OSD project [Ishida et al. 1992], in which "organization" is seen as a (reconfigurable) mapping of capabilities to "agents" (that is, functional specialization) coupled with a distribution of knowledge and control to exploit this specialization so as to mil imlze resource use, called "coordination" or "distributed, network-wide control."
Design is always changing, and never stagnant. In the late 20th century, it was the emergence of Design Thinking that upended how architects, engineers, and industrial design organizations made decisions about how to make new things. Now, the rapid pace of technological advancement has brought forth a new design methodology that will again forever alter the course of design history. Computational design, which takes advantage of mass computing power, machine learning, and large amounts of data, is changing the fundamental role of humans in the design process. Today's infographic comes to us from Schneider Electric, and it looks at how the future of design will be driven by data and processing power.
In this paper, we address the following question: to what extent can organization design be treated as a routine design problem, with a well-defined space o] possibilities and explicit evaluation criteria? The kinds of organizations we are particularly interested in are computational organizations which consist of computational agents that cooperate with one another on their organizational tasks. We present a model of computational organization design that uses predictive knowledge about how exactly various taskenvironmental and organizational factors determine the performance of the organization. Introduction We have been investigating ways to endow a set of agents with the capability to cooperate intelligently under various task environments. Our specific approach has been to give the agents the ability to form and change their task organization under potentially complex, uncertain, and/or dynamic task environments. The process of changing an organization by one or more members of the organization in order to improve performance has been called organization self-design (OSD) in the distributed artificial intelligence (DAI) literature [Corkill, 1983, Corkill and Lesser, 1983, Gasser and Ishida, 1991]. In [So and Durfee, 1993], we have presented a model of OSD which involves an organization design and evaluation component using a definite performance criterion. In this presentation, we elaborate on our model, and address the question of to what extent can organization design be treated as a routine design problem, with a well defined space of possibilities and explicit evaluation criteria.
This article begins with an elaboration of models of design as a process. It then introduces and describes a knowledge representation schema for design called design prototypes. This schema supports the initiation and continuation of the act of designing. Design prototypes are shown to provide a suitable framework to distinguish routine, innovative, and creative design.
I think I can safely say that nobody understands quantum mechanics. LCMD is a dynamic computational/theoretical laboratory, focusing on electronic structure theory in the area of method development, conceptual work and applications relevant to the field of organic electronics and catalysis. We have contributed to the establishment of quantum chemical approaches to describe, identify and quantify non-covalent interactions.